Medical and health informatics Books
Elsevier Health Sciences Bucks StepbyStep Medical Coding 2025 Edition
Book Synopsis
£86.39
Elsevier Health Sciences Bucks Workbook for StepbyStep Medical Coding 2025
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£37.99
Elsevier Health Sciences ICD10CMPCS Coding Theory and Practice 20252026
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£75.59
Elsevier Health Sciences Medical Terminology Anatomy for Coding
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£72.89
Wolters Kluwer Health Systematic Reviews to Answer Health Care
Book SynopsisAccessible, practical, and student-friendly, Systematic Reviews to Answer Health Care Questions, Second Edition, by Dr. Heidi D. Nelson, uses easy-to-understand, step-by-step instruction and real-world examples to illustrate important concepts and principles of today’s systematic reviews. You’ll learn how to form key questions, select evidence, and perform comprehensive reviews not just in predictable circumstances, but when basic rules don’t apply—honing your ability to think critically and solve problems. Perfect for investigators, medical students and faculty, practitioners, policymakers, and others who need to refine their understanding of or approach to systematic reviews, this powerful text goes beyond merely teaching how to catalog and collect, helping readers learn to evaluate, synthesize, and deliver results that will help shape the practice of health care. Provides concise, easy-to-follow instruction on how to conduct a high-quality systematic review that meets current standards in the field—from key question formulation to assessing the quality of included studies and reporting results Features updated methods and revised case studies throughout, along with new chapters on assessing quality and applicability of additional study designs and electronic tools designed to automate or improve efficiency of systematic reviews Covers the essential, practical components of how to perform a systematic review, such as defining a review’s purpose and scope, developing research questions, building a team, and managing the project to maximize efficacy Offers a useful framework to help understand how evidence is evaluated, what it means, its weaknesses or assumptions, and more Shares the knowledge and expertise of Dr. Heidi D. Nelson, a leader in the field of systematic reviews for more than 25 years, whose work has been used in shaping healthcare guidelines and policy in the United States, along with a select group of expert contributing authors An ideal resource for investigators conducting their own systematic reviews; guideline and policy committees tasked with interpreting and applying systematic reviews; students learning the science of research design, critical appraisal, and grading strength of evidence; and practitioners or others outside of health care who need a better understanding of evidence
£57.60
National Geographic Society The Great Age Reboot
Book SynopsisAs the human lifespan increases, New York Times best-selling author Michael Roizen, M.D. offers an inspiring look into the future of longevity--and reveals how to prepare for a longer, healthier future.Believe it or not, living to 100, 120, or even 130 years old will become increasingly common over the next decade--and life past 100 may not be what you think. In this groundbreaking narrative, best-selling author Michael Roizen explains how cutting-edge science and technology will revolutionize your ability to live longer, younger, and better.As evidenced in the global press, today's breakthroughs in longevity research are unprecedented. This provocative yet practical book will help you prepare for the next major social disruptor by making the best decisions for your brain, your body, and your bank account.Dr. Roizen, along with acclaimed economists Peter Linneman and Albert Ratner, unpacks a wide swath of medical phenomena--from reengineer
£18.00
Elsevier Science & Technology Essential MATLAB for Engineers and Scientists
Book SynopsisTable of Contents1. Introduction 2. MATLAB Fundamentals 3. Program Design and Algorithm Development 4. MATLAB Functions and Data Import-Export Utilities 5. Logical Vectors 6. Matrices and Arrays 7. Function M-files 8. Loops 9. MATLAB Graphics 10. Vectors as Arrays and other Data Structures 11. Dynamical Systems 12. Simulation 13. Introduction to Numerical Methods 14. Signal Processing 15. SIMULINK® Toolbox 16. Symbolics Toolbox 17. Complex Variables Applications
£44.96
Facet Publishing Introduction to Healthcare Knowledge and Library
Book SynopsisThe range of roles in healthcare knowledge and library services are many and varied. From ‘traditional’ librarian roles to those that break new ground – including clinical, embedded and outreach librarians and knowledge managers – they are a vital ongoing support for this important sector.This work brings together health information practitioners and researchers with a variety of experience across health information work within knowledge and library services in the NHS. It provides a comprehensive, practitioner-focused introduction to all aspects of knowledge and library work in the health sector with a focus on NHS England. The book begins with an overview of the NHS and how knowledge and library work sit within it. It then addresses such critical areas as services supporting evidence-based practice, the developing area of health information literacy, reflective practice, collaborative working, demonstrating impact and employing digital technology. The book ends with an exploration of what the future might hold for healthcare knowledge and library services such as, the rapid advance of artificial intelligence/machine learning and how it might shape those services and knowledge specialist roles.Knowledge and library specialists offer a valuable gift to healthcare professionals – the ‘gift of time’ enabling them to make informed decisions which directly impact upon patient care. This timely book provides a valuable reference for anyone studying or looking to enter this relevant and diverse field.Table of ContentsForeword by Rob Webster1 An introduction to healthcare knowledge and library services - David Stewart and Gil Young2 Strategic development for healthcare knowledge and library services - Louise Goswami, Alison Day and Holly Case-Wyatt3 Exploring the training and development needs of the healthcare knowledge and library services workforce: a case study Dominic Gilroy and Catherine Mclaren4 Advocacy, and how Knowledge & Library Specialists Tailor Services to meet the Needs of their Stakeholders. Holly Case Wyatt (With special thanks to Vicky Bramwell)5 Mobilising Evidence and Knowledge * Emily Hopkins and Katie Nicholas *6 Internal and External Partnerships Emily Hurt and Dawn Grundy7 Health literacy, patient information and combating misinformation* Joanne Naughton and Geoff Walton*8 Resource Discovery and Open Access Hélène Gorring and Fran Wilkie9 Growing the evidence base in healthcare knowledge and library services Alison Brettle and Ruth Carlyle10 Measuring progress, value, and impact in NHS knowledge and library services Clare Edwards, Dominic Gilroy and Victoria Treadway11 Reflective practice in healthcare settings * Tracey Pratchett, Siobhan Linsey and Rachel Cooke*12 Looking to the future of healthcare knowledge services Sue Lacey-Bryant
£40.00
Elsevier Science Navigating the Maze
Book SynopsisTable of ContentsPART ONE: Past is Prologue1. The early years 1787–18602. The Civil War era and its legacy years 1860–18703. The Gilded Age 1870–19004. A new century: A new America 1900–19255. From depression to global engagement 1925–19456. Donning the mantle of world leadership 1945–19527. Growing pains 1952–19748. A fresh start 1974–1992 PART TWO: Science and Technology Policies in the Modern Age9. Crossing new intersections 1992–200010. Years of anxiety 2001–200811. Recovery and reinvention 2009–201612. Loose change References
£55.05
Pearson Education (US) The AI Revolution in Medicine
Book SynopsisTable of ContentsAuthors' Note Foreword Prologue Chapter 1: First Contact Chapter 2: Medicina ex Machina Chapter 3: The Big Question: Does It “Understand?” Chapter 4: Trust but Verify Chapter 5: The AI-Augmented Patient Chapter 6: So Much More: Math, Coding, and Logic Chapter 7: The Ultimate Paperwork Shredder Chapter 8: Smarter Science Chapter 9: Safety First Chapter 10: The Big Black Bag Epilogue Further Reading Acknowledgments
£20.69
Oxford University Press Inc Live Like Nobody Is Watching
Book SynopsisRespect for patient autonomy and data privacy are generally accepted as foundational western bioethical values. Nonetheless, as our society embraces expanding forms of personal and health monitoring, particularly in the context of an aging population and the increasing prevalence of chronic diseases, questions abound about how artificial intelligence (AI) may change the way we define or understand what it means to live a free and healthy life. Who should have access to our health and recreational data and for what purpose? How can we find a balance between users'' physical safety and their autonomy? Should we allow individuals to forgo continuous health monitoring, even if such monitoring may minimize injury risks and confer health and societal benefits? Would being continuously watched by connected devices ironically render patients more isolated and their data more exposed than ever?Drawing on different use cases of AI health monitoring, this book explores the socio-relational contexTrade ReviewAI-enabled home health monitoring, care delivery and health apps are transforming healthcare. Using the lens of relational autonomy theory, Anita Ho carefully assesses both the potential benefits of these technologies and the ethical challenges they raise for users' autonomy. She demonstrates the importance of situating AI health technologies in a wider socio-relational context, and argues that to truly enhance users' autonomy, these technologies should complement, rather than replace the therapeutic relationship. Timely, informative and thoroughly researched, Ho's book makes an important contribution to contemporary debates about AI and healthcare. * Catriona Mackenzie, Philosophy *Anita Ho parts the fog of technological determinism with moral clarity. Her deeply informed analysis explains the structuring power of AI health monitoring, leading to new understanding of what's at stake for all of us. Live Like Nobody Is Watching is essential reading in graduate programs -- including all health sciences. * Clara Berridge, School of Social Work, University of Washington *Table of ContentsAbbreviations Acknowledgments Preface Introduction Chapter 1: Artificial Autonomy or Relational Intelligence: How Relationality Matters in Health Monitoring Chapter 2: Independent Living With(out) Privacy: AI Home Health Monitoring Chapter 3: Artificial Doctoring: The Case of Direct-to-Consumer Health Monitoring Chapter 4: A Digital Pill to Swallow: AI Monitoring for Medication Adherence and Therapeutic Relationship Chapter 5: From One-Way Mirror to Two-Way Street: Realigning Goals and Practices of AI Health Monitoring Prologue Bibliography Index
£30.59
Oxford University Press Inc Applied Statistics with R
Book SynopsisThis book teaches readers how to analyse data using a programming language called 'R'. R is freely available software and is easily the most widely used program in ecology and evolutionary biology, and is quickly becoming the program-of-choice in other fields such as neuroscience and psychology.
£77.90
Oxford University Press Inc Applied Statistics with R
This book teaches readers how to analyse data using a programming language called 'R'. R is freely available software and is easily the most widely used program in ecology and evolutionary biology, and is quickly becoming the program-of-choice in other fields such as neuroscience and psychology.
£31.34
Oxford University Press Fix IT See and solve the problems of digital
Book SynopsisNew technologies like AI, medical apps and implants seem very exciting but they too often have bugs and are susceptible to cyberattacks. Even well-established technologies like infusion pumps, pacemakers and radiotherapy aren''t immune.Until digital healthcare improves, digital risk means that patients may be harmed unnecessarily, and healthcare staff will continue to be blamed for problems when it''s not their fault.This book tells stories of widespread problems with digital healthcare. The stories inspire and challenge anyone who wants to make hospitals and healthcare better. The stories and their resolutions will empower patients, clinical staff and digital developers to help transform digital healthcare to make it safer and more effective. This book is not just about the bugs and cybersecurity threats that affect digital healthcare. More importantly, it''s about the solutions that can make digital healthcare much safer.Trade ReviewThis is an extraordinary book: a potent and engaging compendium of revelatory stories, bold insights, wise advice, and fresh thinking. * Daniel Jackson (Professor of Computer Science, MIT) *This is a brilliant and hugely enjoyable book which should be compulsory reading for anyone with high-level responsibility for patient care. * Martin Elliott (former Medical Director, Great Ormond Street Hospital for Children) *Table of Contents1: How to read this book PART 1: Diagnosis - riskier than you think 2: We don't know what we don't know 3: Cat Thinking 4: Dogs dancing 5: Fatal overdose 6: Swiss Cheese 7: Victims & second victims 8: Side-effects and scandals 9: The scale of the problem 10: Medical apps and bug blocking PART 2: Treatment - Finding solutions 11: Cars have got safer 12: Safety Two 13: Computational Thinking 14: Risky calculations 15: Who's accountable? 16: Regulation needs fixing 17: Safe and secure 18: Who profits? 19: Interoperability 20: Human Factors 21: Computer Factors 22: User Centered Design 23: Iterative Design 24: Wedge Thinking 25: Attention to detail 26: Planes have got safer 27: Stories for developers 28: Finding bugs 29: Choose safety Part 3: Prognosis - a better future 30: Signs of life 31: The pivotal pandemic? 32: Living happily ever after 33: Good reading 34: Notes 35: Healthcare openness and acknowledgements
£34.49
The University of Chicago Press Life Out of Sequence
Book SynopsisLooks inside this landscape of digital scientific work. This title chronicles the emergence of bioinformatics - the mode of working across and between biology, computing, mathematics, and statistics - from the 1960s to the present, seeking to understand how knowledge about life is made in and through virtual spaces.Trade Review"What happens to biology with computerization? Hallam Stevens's compelling ethnographic and historical narrative shows how the nature of the biological experiment has changed with the increasing use of the tools of information technology in life science and biomedicine." (Hannah Landecker, University of California, Los Angeles)"
£79.80
The University of Chicago Press Life Out of Sequence
Book SynopsisLooks inside this landscape of digital scientific work. This title chronicles the emergence of bioinformatics - the mode of working across and between biology, computing, mathematics, and statistics - from the 1960s to the present, seeking to understand how knowledge about life is made in and through virtual spaces.Trade Review"What happens to biology with computerization? Hallam Stevens's compelling ethnographic and historical narrative shows how the nature of the biological experiment has changed with the increasing use of the tools of information technology in life science and biomedicine." (Hannah Landecker, University of California, Los Angeles)"
£26.60
Elsevier Science Publishing Co Inc Practice Management With Auditing for Coders
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£132.19
Elsevier Health Sciences Bucks StepbyStep Medical Coding 2023 Edition
Book Synopsis
£134.99
Elsevier - Health Sciences Division Fordneys Medical Insurance and Billing
Book SynopsisTable of ContentsUNIT 1 Career Role and Responsibilities 1 Role of an Insurance Billing Specialist 2 Privacy, Security, and HIPAA 3 Compliance, Fraud, and Abuse UNIT 2 Introduction to Health Insurance 4 Basics of Health Insurance 5 The Blue Plans, Private Insurance, and Managed Care Plans 6 Medicare 7 Medicaid and Other State Programs 8 TRICARE and Veterans' Health Care 9 Workers' Compensation 10 Disability Income Insurance and Disability Benefit Programs UNIT 3 Documentation and Coding for Professional Services 11 Medical Documentation and the Electronic Health Record 12 Diagnostic Coding 13 Procedural Coding UNIT 4 Claims Submission in the Medical Office 14 The Paper Claim CMS-1500 15 The Electronic Claim UNIT 5 The Claim Follow-Up and Payment Process 16 Receiving Payments and Insurance Problem Solving 17 Collection Strategies UNIT 6 Health Care Facility Billing 18 Introduction to Health Care Facilities and Ambulatory Surgery Centers 19 Billing for Health Care Facilities UNIT 7 Employment 20 Seeking a Job and Attaining Professional Advancement
£107.34
Elsevier - Health Sciences Division Workbook for Fordneys Medical Insurance and
Book SynopsisTable of ContentsUnit One: Career Roles and Responsibilities 1. Role of an Insurance Billing Specialist 2. Privacy, Security and HIPAA 3. Compliance, Fraud and Abuse Unit Two: Introduction to Health Insurance 4. Basics of Health Insurance 5. The Blue Plans, Private Insurance and Managed Care Plans 6. Medicare 7. Medicaid and Other State Programs 8. TRICARE and Veteran's Health Care 9. Workers Compensation 10. Disability Income Insurance and Disability Benefit Insurance Unit Three: Documentation and Coding for Professional Services 11. Medical Documentation and the Electronic Health Record 12. Diagnostic Coding 13. Procedural Coding Unit Four: Claims Submission in the Medical Office 14. The Paper Claim CMS-1500 15. The Electronic Claim Unit Five: The Claim Follow-Up and Payment Process 16. Receiving Payments and Insurance Problem Solving 17. Collection Strategies Unit Six: Healthcare Facility Billing 18. Ambulatory Surgery Center 19. Hospital Outpatient and Inpatient Billing Unit Seven: Employment 20. Seeking a Job and Attaining Professional Advancement
£38.94
Elsevier - Health Sciences Division Bucks 2023 Coding Exam Review
Book SynopsisTable of ContentsPart 1: Anatomy, Terminology, and Pathophysiology 1 Integumentary System 2 Musculoskeletal System 3 Respiratory System 4 Cardiovascular System 5 Female Genital System and Pregnancy 6 Male Genital System 7 Urinary System 8 Digestive System 9 Mediastinum and Diaphragm 10 Hemic and Lymphatic System 11 Endocrine System 12 Nervous System 13 Senses Part 2: Physician-based Reimbursement Issues 14 Physician-based Reimbursement Issues Part 3: Facility-based Reimbursement Issues 15 Facility-based Reimbursement Issues Part 4: CPT and HCPCS Coding 16 Introduction to CPT 17 Evaluation and Management (E/M) Section (99202-99499) 18 Anesthesia Section (00100-01999) 19 CPT/HCPCS Level I Modifiers (-22 to -99) 20 Surgery Section (10004-69990) 21 Radiology Section (70010-79999) 22 Pathology and Laboratory Section (80047-89398, 0001U-0354U) 23 Medicine Section (90281-99607) 24 HCPCS Coding Part 5: ICD-10-CM and ICD-10-PCS Coding 25 ICD-10-CM Overview 26 Using ICD-10-CM 27 ICD-10-CM Chapters 1-10 28 ICD-10-CM Chapters 11-14 29 ICD-10-CM Chapters 15-22 30 Outpatient Coding 31 ICD-10-PCS, Reporting Inpatient Procedures Part 6: Physician-based Examinations 32 Physician-based Examinations Part 7: Facility-based Examinations 33 Facility-based Examinations Appendix A Resources Appendix B Answers Appendix C Medical Terminology Appendix D Combining Forms Appendix E Prefixes Appendix F Suffixes Appendix G Abbreviations Appendix H Further Text Resources Appendix I Pharmacology Review Index
£68.39
Elsevier - Health Sciences Division Foundations of Health Information Management
Book SynopsisTable of ContentsUnit 1: The Environment of Health Care 1. The Health Care Industry 2. Collecting and Storing Health Care Data Unit 2: Content, Structure, and Processing of Health Information 3. Sources of Data 4. Data Quality and Management 5. Coded Data Unit 3: Use and Analysis of Data 6. Financial Management 7. Statistics and Data Analytics Unit 4: Administration and Operations 8. Confidentiality and Compliance 9. Management and Leadership 10. Performance Improvement and Project Management Appendix A Paper Health Records Appendix B Electronic Documentation Appendix C Using Microsoft Excel to Perform Calculations Glossary Index Abbreviations
£73.14
Elsevier - Health Sciences Division Workbook for Beiks Health Insurance Today
Book SynopsisTable of ContentsUNIT ONE: BUILDING A FOUNDATION Chapter 1: The Origins of Health Insurance Chapter 2: Tools of the Trade: A Career as a Health Insurance (Medical) Professional Chapter 3: The Legal and Ethical Side of Health Insurance Chapter 4: Healthcare Reform: Coverage Types and Sources Chapter 5: The Patient and the Billing Process UNIT TWO: HEALTH INSURANCE BASICS Chapter 6: Reimbursement Models Chapter 7: Understanding Managed Care Chapter 8: Understanding Medicare Chapter 9: Understanding Medicaid Chapter 10: Understanding Military Carriers Chapter 11: Understanding Miscellaneous Carriers: Workers' Compensation and Disability Insurance UNIT THREE: CLAIMS SUBMISSION Chapter 12: Claim Submission Methods Chapter 13: Diagnostic Coding Chapter 14: Procedural, Evaluation and Management, and HCPCS Coding Chapter 15: Claims Management UNIT FOUR: ADVANCED APPLICATION Chapter 16: The Role of Computers in Health Insurance Chapter 17: Reimbursement Procedures: Getting Paid Chapter 18: Hospital Billing and the UB-04 Appendix: Blank Forms
£37.79
Elsevier Science & Technology Theranostics and Precision Medicine for the
Book SynopsisTable of Contents1. Clinical and safety assessment of the HCC patients2. Liver transplantation for HCC therapy3. Clinical trials for HCC in the diagnosis and therapy: An international perspective4. Recent advancements in immunotherapy interventions for the management of HCC5. Role of genetic insights and tumor microenvironment in HCC: New opportunities for gene therapy6. An Update on the treatment of hepatocellular carcinoma7. An update of image-based surveillance in HCC8. Meta-analysis of PD-1/PD-L1 inhibitors in advanced HCC9. Towards a personalized medicine approach for the treatment of HCC10. Precision medicine in the theranostics of HCC11. Immunohistology of HCC-enabled precision medicine12. Artificial Intelligence and Precision Medicine for HCC13. Genomics-Enabled Precision Medicine for HCC
£95.25
WW Norton & Co Fragmented
Book SynopsisAn award-winning physician-writer exposes how pervasive cracks in the health care system cost us time, energy, and lives—and how we can fix them.Trade Review"Yurkiewicz is working against the grain of American health care, in which patients are assumed to be consumers, not managers of it. . . . [Her] book is a detailed, moving portrait of what medicine could look like." -- Leah Libresco Sargeant - National Review"Illuminating case studies drive home the dire consequences of fragmentation . . . Persuasive and damning, this scathing indictment unsettles." -- Publishers Weekly (starred review)"Moving . . . Yurkiewicz’s poignant prose reads like a novel . . . An engaging read that paints an honest picture of how a broken system impacts patients and providers." -- Kirkus"Yurkiewicz makes a frightening and compelling case against a medical system that doesn’t promote—and often hinders—communication among medical caregivers, to the detriment of patients . . . An informative and sobering look at the state of patient care in the United States." -- Library Journal"Fragmented is a bravura feat of synthesis, showing how so many failings of America’s health care system are actually facets of the same horrible problem. It’s a call to arms, showing that said problem is intolerable and fixable. It’s an essential book, possessed of a ferocious urgency and anchored by Ilana Yurkiewicz’s stirring, compassionate writing." -- Ed Yong, New York Times best-selling author and winner of the Pulitzer Prize"A beautiful meditation on and exposé of the failures and opportunities in American health care. Ilana Yurkiewicz brings her singular voice—as a brilliant doctor scrabbling to provide top-notch care, a vulnerable daughter actively bridging gaps during her own father’s serious illness, and an expert observer of systems and policy—to this crucial book full of empathy, gripping stories, and hard-won wisdom about how to achieve better care for us all. I loved it." -- Lucy Kalanithi, MD, Stanford School of Medicine, and widow of Paul Kalanithi, author of When Breath Becomes Air"American health care is so technically advanced, the spawning ground for life-changing medical breakthroughs, yet it fails so many by being dysfunctional, absurdly costly, and uneven . . . Ilana Yurkiewicz combines lucid prose, astute observations as a frontline provider, and incredible empathy to dissect this paradox in an unforgettable way . . . An important book." -- Abraham Verghese, author of The Covenant of Water and Cutting for Stone"Urgent, timely, and eye-opening." -- Danielle Ofri, MD, PhD, author of When We Do Harm"A lucid diagnosis of the systemic problem that has resulted in our ‘broken’ health-care system. Yurkiewicz allows readers to see through a young doctor's eyes as the reality of fragmentation dawns during intensely emotional situations, infusing compelling narratives with humor and humanity, and making sense of inscrutable health policy issues that affect us all. Somehow, amid the chaos, Fragmented is able to find a glimmer of hope that is desperately needed." -- James Hamblin, MD, author of Clean"Fragmented is a riveting, impassioned narrative that details the Kafka-esque paradox of American medicine: Despite having access to more information than ever, our doctors seem to know less and less about us. What makes it so uplifting and inspiring is that Yurkiewicz, an oncologist who has witnessed this problem first-hand, is optimistic that these challenges can be overcome—and that a more compassionate, humane healthcare system is within reach." -- Seth Mnookin, New York Times best-selling author and professor of science writing, Massachusetts Institute of Technology"From the intimacy of the hospital wards and her relationships with her own patients, Yurkiewicz tells the compelling story of the razor-thin margins by which medical care is delivered successfully in the United States, and how easily people can slip through the cracks of our health system. A must-read." -- Mikkael A. Sekeres, MD, MS, author of Drugs and the FDA and When Blood Breaks Down
£23.39
Elsevier Health Sciences Fordneys Medical Insurance and Billing
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£106.19
Elsevier Science Resilient Health
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£97.75
Elsevier Health Sciences Bucks The Next Step Advanced Medical Coding and
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£80.09
Elsevier Health Sciences Bucks Coding Exam Review 2025
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£76.49
Elsevier Health Sciences Bucks 2025 HCPCS Level II
Book Synopsis
£77.39
Elsevier Health Sciences Bucks 2025 ICD10PCS
Book Synopsis
£77.39
Elsevier Health Sciences Bucks 2024 Step by Step Textbook and Bucks 2024
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£128.79
Elsevier Health Sciences Bucks 2025 ICD10CM For Physicians AMA 2025 CPTÂ
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£243.89
Elsevier Health Sciences Bucks 2025 StepbyStep Textbook and Bucks 2025
Book Synopsis
£110.69
Elsevier Health Sciences Bucks 2026 ICD10CM for Physicians
£83.69
Elsevier Health Sciences Bucks 2026 ICD10CM for Hospitals
£84.59
Elsevier Health Sciences Bucks 2026 ICD10PCS
Book Synopsis
£86.99
John Wiley & Sons Inc Bioinformatics for Vaccinology
Book SynopsisThe recent expansion in genome data and the parallel increase in cheap computing power has placed the bioinformatics exploration of pathogen genomes centre stage for vaccine researchers. The book shows how bioinformatic techniques can solve key problems from vaccinology and immunology.Trade Review“It pulls a number of different disciplines into a concise review that illustrates the potential we have in science to change our world.” (Doody's, April 2009) "This book may well serve as a first line of reference for all biologists and computer scientists. This textbook would be an excellent addition to the bookshelf of most scientists who encounter vaccinology in the drug discovery and development processes." ( Virology Journal - October -2009) Table of ContentsPreface xiii Acknowledgements xv Exordium xvii 1 Vaccines: Their place in history 1 Smallpox in history 1 Variolation 3 Variolation in history 5 Variolation comes to Britain 6 Lady Mary Wortley Montagu 9 Variolation and the Sublime Porte 11 The royal experiment 13 The boston connection 14 Variolation takes hold 17 The Suttonian method 18 Variolation in Europe 19 The coming of vaccination 21 Edward Jenner 23 Cowpox 26 Vaccination vindicated 28 Louis Pasteur 29 Vaccination becomes a science 30 Meister, Pasteur and rabies 31 A vaccine for every disease 33 In the time of cholera 34 Haffkine and cholera 36 Bubonic plague 37 The changing face of disease 39 Almroth wright and typhoid 40 Tuberculosis, Koch, and Calmette 43 Vaccine BCG 44 Poliomyelitis 46 Salk and Sabin 47 Diphtheria 49 Whooping cough 50 Many diseases, many vaccines 51 Smallpox: Endgame 53 Further reading 54 2 Vaccines: Need and opportunity 55 Eradication and reservoirs 55 The ongoing burden of disease 57 Lifespans 57 The evolving nature of disease 59 Economics, climate and disease 60 Three threats 60 Tuberculosis in the 21st century 61 HIV and AIDS 62 Malaria: Then and now 63 Influenza 64 Bioterrorism 65 Vaccines as medicines 67 Vaccines and the pharmaceutical industry 68 Making vaccines 70 The coming of the vaccine industry 70 3 Vaccines: How they work 73 Challenging the immune system 73 The threat from bacteria: Robust, diverse, and endemic 74 Microbes, diversity and metagenomics 75 The intrinsic complexity of the bacterial threat 76 Microbes and humankind 77 The nature of vaccines 78 Types of vaccine 80 Carbohydrate vaccines 82 Epitopic vaccines 82 Vaccine delivery 83 Emerging immunovaccinology 84 The immune system 85 Innate immunity 86 Adaptive immunity 88 The microbiome and mucosal immunity 90 Cellular components of immunity 90 Cellular immunity 93 The T cell repertoire 93 Epitopes: The immunological quantum 94 The major histocompatibility complex 95 MHC nomenclature 97 Peptide binding by the MHC 98 The structure of the MHC 99 Antigen presentation 101 The proteasome 101 Transporter associated with antigen processing 103 Class II processing 103 Seek simplicity and then distrust it 104 Cross presentation 105 T cell receptor 106 T cell activation 108 Immunological synapse 109 Signal 1, signal 2, immunodominance 109 Humoral immunity 110 Further reading 112 4 Vaccines: Data and databases 113 Making sense of data 113 Knowledge in a box 114 The science of -omes and -omics 115 The proteome 115 Systems biology 116 The immunome 117 Databases and databanks 118 The relational database 119 The XML database 119 The protein universe 120 Much data, many databases 122 What proteins do 122 What proteins are 124 The amino acid world 124 The chiral nature of amino acids 127 Naming the amino acids 130 The amino acid alphabet 132 Defining amino acid properties 134 Size, charge and hydrogen bonding 135 Hydrophobicity, lipophilicity and partitioning 136 Understanding partitioning 139 Charges, ionization, and pka 140 Many kinds of property 143 Mapping the world of sequences 146 Biological sequence databases 147 Nucleic acid sequence databases 148 Protein sequence databases 149 Annotating databases 150 Text mining 151 Ontologies 153 Secondary sequence databases 154 Other databases 155 Databases in immunology 156 Host databases 156 Pathogen databases 159 Functional immunological databases 161 Composite, integrated databases 162 Allergen databases 163 Further reading 165 Reference 165 5 Vaccines: Data driven prediction of binders, epitopes and immunogenicity 167 Towards epitope-based vaccines 167 T cell epitope prediction 168 Predicting MHC binding 169 Binding is biology 172 Quantifying binding 173 Entropy, enthalpy and entropy-enthalpy compensation 174 Experimental measurement of binding 175 Modern measurement methods 177 Isothermal titration calorimetry 178 Long and short of peptide binding 179 The class I peptide repertoire 180 Practicalities of binding prediction 181 Binding becomes recognition 182 Immunoinformatics lends a hand 183 Motif based prediction 184 The imperfect motif 185 Other approaches to binding prediction 186 Representing sequences 187 Computer science lends a hand 188 Artificial neural networks 188 Hidden Markov models 190 Support vector machines 190 Robust multivariate statistics 191 Partial least squares 191 Quantitative structure activity relationships 192 Other techniques and sequence representations 193 Amino acid properties 194 Direct epitope prediction 195 Predicting antigen presentation 196 Predicting class II MHC binding 197 Assessing prediction accuracy 199 ROC plots 202 Quantitative accuracy 203 Prediction assessment protocols 204 Comparing predictions 206 Prediction versus experiment 207 Predicting B cell epitopes 208 Peak profiles and smoothing 209 Early methods 210 Imperfect B cell prediction 211 References 212 6 Vaccines: Structural approaches 217 Structure and function 217 Types of protein structure 219 Protein folding 220 Ramachandran plots 221 Local structures 222 Protein families, protein folds 223 Comparing structures 223 Experimental structure determination 224 Structural genomics 226 Protein structure databases 227 Other databases 228 Immunological structural databases 229 Small molecule databases 230 Protein homology modelling 231 Using homology modelling 232 Predicting MHC supertypes 233 Application to alloreactivity 235 3D-QSAR 236 Protein docking 238 Predicting B cell epitopes with docking 238 Virtual screening 240 Limitations to virtual screening 241 Predicting epitopes with virtual screening 243 Virtual screening and adjuvant discovery 244 Adjuvants and innate immunity 245 Small molecule adjuvants 246 Molecular dynamics and immunology 248 Molecular dynamics methodology 249 Molecular dynamics and binding 249 Immunological applications 250 Limitations of molecular dynamics 251 Molecular dynamics and high performance computing 252 References 253 7 Vaccines: Computational solutions 257 Vaccines and the world 257 Bioinformatics and the challenge for vaccinology 259 Predicting immunogenicity 260 Computational vaccinology 261 The threat remains 262 Beyond empirical vaccinology 262 Designing new vaccines 263 The perfect vaccine 264 Conventional approaches 265 Genome sequences 266 Size of a genome 267 Reverse vaccinology 268 Finding antigens 269 The success of reverse vaccinology 271 Tumour vaccines 273 Prediction and personalised medicine 275 Imperfect data 276 Forecasting and the future of computational vaccinology 277 Index 283
£77.36
John Wiley & Sons Inc Cancer Bioinformatics
Book SynopsisThe development and application of bioinformatics tools to basic and translational cancer research is, in fact, a rapidly expanding field that deserves a timely review. Therefore, a publication of this type is needed. The editors have done an excellent job in recruiting well-established scientists to author the various chapters of the book. Dieter Naf, Jackson Laboratory, USA Cancer bioinformatics is now emerging as a new interdisciplinary field, which is facilitating an unprecedented synthesis of knowledge arising from the life and clinical sciences. This groundbreaking title provides a comprehensive and up-to-date account of the enormous range of bioinformatics for cancer therapy development from the laboratory to clinical trials. It functions as a guide to integrated data exploitation and synergistic knowledge discovery, and support the consolidation of the interdisciplinary research community involved.Trade Review"…recommended for purchase for medical, academic or special libraries serving basic or clinical cancer researchers and bioinformaticists." (E-STREAMS, September 2007) "…good reading for anyone entering into some aspect of cancer research, whether it is biological, mathematical, or computational…" (Biometrics, December 2006) "Overall … an excellent and well-edited book that could be read from cover to cover or used as a reference." (British Journal of Healthcare Computing and Information Management, July 2006)Table of ContentsPreface. List of Contributors. SECTION I CANCER SYSTEMS. 1 A Path to Knowledge: from Data to Complex Systems Models of Cancer (Sylvia Nagl). 1.1 Conceptual foundations: biological complexity. 1.2 A taxonomy of cancer complexity. 1.3 Modelling and simulation of cancer systems. 1.4 Data standards and integration. 1.5 Concluding remarks. 2 Theory of Cancer Robustness (Hiroaki Kitano). 2.1 Robustness: the fundamental organizational principle of biological systems. 2.2 Underlying mechanisms for robustness. 2.3 Intrinsic features of robust systems: evolvability and trade-offs. 2.4 Cancer as a robust system. 2.5 Therapy strategies. 2.6 A proper index of treatment efficacy. 2.7 Computational tools. 2.8 Conclusion. 3 Developing an Integrated Informatics Platform for Cancer Research (Richard Begent). 3.1 Background. 3.2 The challenge. 3.3 The UK National Cancer Research Institute (NCRI) informatics platform. 3.4 Developing the informatics platform. 3.5 Benefits of the platform. 3.6 Conclusions. SECTION II In silico MODELS. 4 Mathematical Models of Cancer (Manish Patel and Sylvia Nagl). 4.1 Growth models. 4.2 A very brief tour of cellular automata. 4.3 Angiogenesis models. 4.4 Treatment response models. 4.5 Dynamic pathways models. 4.6 Other models. 4.7 Simulations of complex biological systems. 4.8 Concluding remarks. 5 Some Mathematical Modelling Challenges and Approaches in Cancer (Philip Maini and Robert A. Gatenby). 5.1 Introduction. 5.2 Multiscale modelling. 5.3 Tumour vascular modelling. 5.4 Population models. 5.5 Conclusion. 6 Computer Simulation of Tumour Response to Therapy (Georgios S. Stamatakos and Nikolaos Uzunoglu). 6.1 Introduction. 6.2 Tumour growth simulation. 6.3 Radiotherapy response simulation. 6.4 Chemotherapy response simulation. 6.5 Simulation of tumour response to other therapeutic modalities. 6.6 Simulation of normal tissue response to antineoplastic interventions. 6.7 Integration of molecular networks into tumour behaviour simulations. 6.8 Future directions. 7 Structural Bioinformatics in Cancer (Stephen Neidle). 7.1 Introduction. 7.2 Macromolecular crystallography. 7.3 Molecular modelling. 7.4 Conclusions. SECTION III In vivo MODELS. 8 The Mouse Tumour Biology Database: an Online Resource for Mouse Models of Human Cancer (Carol J. Bult, Debra M. Krupke, Matthew J. Vincent, Theresa Allio, John P. Sundberg, Igor Mikaelian and Janan T. Eppig). 8.1 Introduction. 8.2 Background. 8.3 Database content. 8.4 Data acquisition. 8.5 Using the MTB database. 8.6 Connecting the MTB database with related databases. 8.7 Summary. 9 Bioinformatics Approaches to Integrate Cancer Models and Human Cancer Research (Cheryl L. Marks and Sue Dubman). 9.1 Background. 9.2 The MMHCC Informatics at the outset of the programme. 9.3 Initial NCI bioinformatics infrastructure development. 9.4 Future directions for informatics support. 9.5 Summary. SECTION IV DATA. 10 The FAPESP/LICR Human Cancer Genome Project: Perspectives on Integration (Ricardo Brentani, Anamaria A. Camargo, Helena Brentani and Sandro J. De Souza). 10.1 Introduction. 10.2 The FAPESP/LICR Human Cancer Genome Project. 10.3 An integrated view of the tumour transcriptome. 10.4 Summary. 11 Today’s Science, Tomorrow’s Patient: the Pivotal Role of Tissue, Clinical Data and Informatics in Modern Drug Development (Kirstine Knox, Amanda Taylor and David J. Kerr). 11.1 Introduction. 11.2 A new national strategy for the provision of tissue annotated with clinical information to meet current and future needs of academic researchers and industry. 11.3 The NCRI National Cancer Tissue Resource for cancer biology and treatment development. 11.4 A potential future world-class resource integrating research and health service information systems and bioinformatics for cancer diagnosis and treatment. 11.5 A proposed information system architecture that will meet the challenges and deliver the required functionality: an overview. 11.6 Consent and confidentiality: ensuring that the NCTR is embedded in the UK’s legal and ethical framework. 11.7 Concluding remarks: future challenges and opportunities. SECTION V ETHICS. 12 Software Design Ethics for Biomedicine (Don Gotterbarn and Simon Rogerson). 12.1 The problem: software and research. 12.2 Risk identification. 12.3 Biomedical software example. 12.4 Is an ethical risk analysis required? 12.5 Details of SoDIS. 12.6 A SoDIS analysis of the biomedical software example. 12.7 Conclusion. 13 Ethical Issues of Electronic Patient Data and Informatics in Clinical Trial Settings (Dipak Kalra and David Ingram). 13.1 Introduction. 13.2 Ethical aspects of using patient-identifiable health data. 13.3 Legislation and policies pertaining to patient-identifiable health data. 13.4 Using anonymized and pseudonymized data. 13.5 Protecting personal health data. 14 Pharmacogenomics and Cancer: Ethical, Legal and Social Issues (Mary Anderlik Majumder and Mark Rothstein). 14.1 Introduction. 14.2 Getting pharmacogenomic tests and drugs to market. 14.3 Cost and coverage issues. 14.4 Ethical challenges of pharmacogenomics. 14.5 Conclusion. Index
£117.75
University of California Press When A Doctor Hates A Patient
Book Synopsis
£64.00
University of California Press Ben Cao Gang Mu Volume VI
Book SynopsisVolume VI in theBen cao gang museries offers a complete translation of chapters 26 through 33, devoted to vegetables and fruits. TheBen cao gang muis a sixteenth-century Chinese encyclopedia of medical matter and natural history by Li Shizhen (15181593). The culmination of a sixteen-hundred-year history of Chinese medical and pharmaceutical literature, it is considered the most important and comprehensive book ever written in the history of Chinese medicine and remains an invaluable resource for researchers and practitioners. This nine-volume series reveals an almost two-millennia-long panorama of wide-ranging observations and sophisticated interpretations, ingenious manipulations, and practical applications of natural substances for the benefit of human health. Paul U. Unschuld's annotated translation of theBen cao gang mu, presented here with the original Chinese text, opens a rare window into viewing the people and culture of China's past. Table of ContentsContents 1. Prolegomena 1.1 History of Chinese materia medica literature 1.2 Structure and contents of the Ben cao gang mu 1.3 Biographical sketch of Li Shizhen (1518 – 1593) 2. Notes on the Translation 3. Wang Shizhen’s preface of 1590 4. Translation of the Ben Cao Gang Mu , ch. 26 through 33 Vegetables I, Fragrant-Acrid [Items], Chapter 26 Vegetables II, Soft[ing] and Smooth[ing items], Chapter 27 Vegetables III, Melons, Chapter 28 Vegetables IV, Water Vegetables Vegetables V, Mushrooms-Fungi Fruits I, Five Fruits, Chapter 29 Fruits II, Mountain Fruits, Chapter 30 Fruits III, Non-Chinese Fruits, Chapter 31 Fruits IV, Spices, Chapter 32 Fruits V, Melons and Berries Chapter 33 Fruits VI, Water Fruits Appendix
£127.20
T.S.Aguilar Lifeline The Case for Effective Cancer
Book Synopsis
£21.25
Taylor & Francis Ltd A Researchers Guide to Using Electronic Health
Book SynopsisIn an age when electronic health records (EHRs) are an increasingly important source of data, this essential textbook provides both practical and theoretical guidance to researchers conducting epidemiological or clinical analysis through EHRs.Table of Contents1: The Rise of Electronic Health Records. 2: Concepts in Electronic Health Record Research. Section I: EHR Data for Research. 3: Planning for Electronic Health Record Research. 4: Accessing Electronic Health Record Data. 5: Data Management. 6: Perils of Electronic Health Record Data. Section II: Epidemiology and Data Analysis. 7: Study Design and Sampling Strategies. 8: Epidemiologic Measures. 9: Bias and Validity in Observational Research. 10: Epidemiologic Analysis I. 11: Epidemiologic Analysis II. 12: Advanced and Emerging Methods and Applications. Section III: Interpretation to Application. 13: Publication and Presentation. 14: Applications of Electronic Health Record Research. 15: Case Studies in Electronic Health Record Research. Appendix 1: Secondary Data Research Planner. Appendix 2: Example Code using R.
£35.14
Taylor & Francis Ltd Digital Transformation in Healthcare
Book SynopsisIn an era of digital transformation within healthcare management, this important book outlines an ecosystem perspective to illustrate how a range of actors can use digital technologies to offer better value within the provision of healthcare services. From mobile applications to point-of-care diagnostic devices, from AI-enabled applications for data analysis to cloud models for service delivery and blockchain infrastructures, it provides a roadmap for how healthcare organizations can leverage these digital technologies. The book is also illustrated with case studies from different areas, including software for medical diagnostics, blockchain infrastructures for use in pharmaceutical supply chains and clinical trials, and federated learning platforms for genomics. Covering key issues such as patients' rights to data and written in the aftermath of the COVID-19 pandemic, the book will be essential reading for researchers, postgraduate students, and professionals interested in Trade Review“This is a valuable book that comes at a critical time, when digital health has accelerated across the globe fanned by the fire of the pandemic. It provides an informed account of the factors to consider and practical steps to make the most of the opportunity.”Tara Donelly, Founder Digital Care, Ex-Chief Digital Officer, NHS Digital“Digital healthcare is not merely a subset of traditional healthcare; it represents a reconfiguration of the entire healthcare system. Therefore, any effort to digitally transform organisations and effectively prepare them for the future must adopt an ecosystem approach. This book offers a practical framework for implementing this approach, highlighting the necessity for collective action as no single organisation can undertake this transformation alone.”Jorge Armanet, Entrepeneur, Operator Investor, and Advisor. Founder and Former CEO of HealthUnlocked. Cambridge Digital Innovation Fellow.“This book gives excellent insight into the benefits, risks and their mitigation of the use of digital technologies in healthcare. It then covers proposals on how we should regulate and respond to these new technologies to avoid the risks this new paradigm brings. I would recommend this book to anyone working in digital healthcare.”Stephen Critchlow, Founder, CEO and Chair of Wellbeing Team at Evergreen Life, Chair of the NIHR AI in Healthcare Board.“This book illustrates the key changes in the industry when COVID-19 accelerated digital healthcare. When I first presented patient portals in the UK it was something the NHS could not see would be used or adopted. Data silos cause so much complexity and create gaps in patient records. As these challenges are addressed we start to see the value being created and this is a process explored in this book. The book offers a comprehensive understanding of the complexity of digital transformation in healthcare.”Chris Rushworth, Head of Product, Doctor Care Anywhere“This is an important book. We are facing a global health crisis and the current ‘egosystem’ approach is never going to scale and offer the right economics to address the global need. This book illustrates how digital technologies can create and transform health ecosystems in way that was never possible and how these digital arenas change the economics of the market allowing greater participation and delivering additional value to those participants. The framework it offers provides a pragmatic guide to the journey to this ecosystem model, allow the reader to embark on the journey without the associated risks such undertakings often attract. Highly recommended.”Marcus Robbins, Chief Digital Advisor - Head of Strategy and Growth - DX Services – Fujitsu UK“This rich and engaging book about contemporary challenges in healthcare offers a unique perspective. Targeting practitioners and managers, it operationalises key insights from otherwise hard-to-get academic discussions by carefully selecting, presenting and illustrating these in accessible form -- without trivialising them.”Eric Monteiro, Professor of information systems, Norwegian University of Science and Technology“Professor Constantinides brilliantly navigates healthcare's digital transformation using powerful concepts and vivid examples. His framework illuminates how ecosystem strategy, technology, and human resources empower diverse actors to co-innovate and co-create value. Thoughtfully balancing the possibilities and risks of disruptive technologies like Generative AI and blockchain, he provides an indispensable roadmap for this evolving landscape. A must-read for anyone vested in the future of healthcare!”Arun Rai, Regents’ Professor and Howard S. Starks Distinguished Chair, Georgia State University“’Digital Transformation in Healthcare: An Ecosystem Approach’ by Professor Constantinides expertly traverses the healthcare landscape. Highlighting the importance of partnerships, digital platforms, and an ecosystem perspective, it offers strategic co-innovation insights for value creation. The book incisively illuminates the potentials of Generative AI, learning infrastructures, and blockchain technologies. An indispensable guide, the book offers profound insights into digital transformation for anyone in healthcare.”Elena Karahanna, Distinguished Research Professor and C. Herman & Mary Virginia Terry Distinguished Chair in Business Administration, University of Georgia“In Digital Transformation in Healthcare: An Ecosystem Approach, Panos Constantinides provides much-needed guidance for healthcare managers, indeed all managers. They take a “show, don’t tell” approach by methodically showing the steps, with examples, that organizations must follow to digitally transform their operations and strategy. The ecosystem approach is necessary for the future success of healthcare organizations so that they can focus on their core competency of providing health services in an efficient and effective manner.”Rajiv Kohli, John N. Dalton Memorial Professor of Business, Raymond A. Mason School of Business, William & Mary University“Corporations tend to focus on the efficiency gains from digital transformation but, often, fail to see the real transformative power that digital technologies provide: the ability to re-imagine the new possible to achieve what most actors from the established value chain would consider impossible. This timely and comprehensive book is all about the “impossible-new possible” in healthcare through digital transformation, and the enabling role played by digital technologies and ecosystems. Panos Constantinides presents a compelling framework for healthcare organizations to navigate the complex landscape of digital transformation. From telemedicine and blockchain to federated learning and generative AI technologies, this book provides a rich journey into how ecosystem approaches can activate collaborative partnerships and collective action to unlock innovation and drive transformative change in healthcare solutions. It is a “must read” for healthcare organizations, policymakers, and empowered patients alike who want to shape the new possible.”Carmelo Cennamo, Professor Copenhagen Business School"Digital Transformation in Healthcare: An Ecosystem Approach" tackles some of the most complex challenges in a critical industry and carefully develops the what, why, and how. Using concrete examples, the book lays out the key value propositions and architecture, makes the case for the need to change, and develops actionable strategies to make it happen while managing the risks and governance challenges that are sure to arise. I highly recommend it as a key manual to create positive change in healthcare.”Geoffrey Parker, Co-author of Platform Revolution, Charles E. Hutchinson '68A Professor of Engineering Innovation Dartmouth CollegeTable of ContentsPART 1. SETTING THE SCENE: THE HEALTHCARE CONTEXT. 1.Disruption and Digital Transformation in Healthcare. 2.Complexity in Healthcare Services. 3.Organizational Change and Digital Maturity. PART 2.DIGITAL TRANSFORMATION ACROSS HEALTHCARE ECOSYSTEMS. 4.An Ecosystem Approach to Digital Transformation. 5.Blockchain Infrastructures in Healthcare. 6.Cloud Computing and Federated Learning Infrastructures. PART 3.GENERATIVE TRANSFORMATION, THE RACE TO TECH ARMS AND REGULATION. 7.Generative Transformation and Regulatory Challenges.
£34.19
Taylor & Francis Ltd Health Informatics
Book SynopsisTrue wellness innovation requires the recruitment of multi-disciplinary participants. This book breaks the mold with examples from healthcare experts and other professionals who have leveraged informatics to better the lives of their constituents. Jason Helgerson, Founder & CEO, Helgerson Solutions Group LLCDeveloped for those training in academic centers as well as for those already out in the field, this book looks at how attorneys, behavioral health experts, business development experts, chief information officers, chief medical officers, chief nursing information officers, consumer advocates, cryptographic experts, futurists, geneticists, informaticists, managed care executives, nurses, pharmacists, physicians, public health professionals, software developers, systems security officers, and workforce experts are collaborating on a team-based, IT-enabled approach to improve healthcare.Trade Review"Dr. Volpe has produced an excellent work in the field of informatics where the intersection of clinical pathways, technology, change management, and psychology cohabitate. Everyone interested in this field should read the appropriate chapters so that they are comfortable with this comprehensive field." Sam Amifar MD MS ABP-CI,CMIO CIO The Brooklyn Hospital Center"This text presents a multi-disciplinary view of health informatics, offering perspectives to help us better understand the successes, challenges, as well as opportunities towards a more equitable healthcare system that prioritizes patient care and public health."Vibhuti Arya, PharmD, MPH, FAPhA | Curating Brave SpacesGlobal Lead, Gender Equity and Diversity Workforce DevelopmentInternational Pharmaceutical Federation (FIP)Professor, St. John's University"Health Informatics Multidisciplinary Approaches for Current and Future Professionals is essential reading for policy makers, doctors, administrators and frontline healthcare workers. The book illustrates that deep integration by and between all aspects of care delivery, including IT, employee training and education, finance, and clinical practice will produce improved health outcomes and reduced costs."John August, Program Director, Partners Program, ILR Scheinman Institute, ILR School, Cornell University"As health care advances, there is more patient data in different platforms ranging from providers to insurance plans. The need for timely patient data exchange and integration is even more imperative to achieve a holistic picture of the patient from the realms of medical, behavioral health and social determinants of health services. This welcome edition brings together the many disciplines and perspectives to enhance the understanding of the many opportunities that informatics and health IT play towards transforming patient care and population health."Peggy Chan, MPH – former NYS DOH DSRIP Director"This book eclipses many others with the expansiveness of the contributions from so many accomplished authors. The foundation of 21st century healthcare is the use of effective and ethical use of informatics. The space has moved from niche to center stage - it is in this context that the next innovators in technology and patient care will find their opportunity."Joseph Conte, PhD, CPHQ, Executive Director Staten Island Performing Provider System"Dr. Volpe has created perhaps the first truly comprehensive book on Health Informatics in print. Its breadth of coverage is truly inspiring. It should become a required text for the rapidly increasing number of online, hybrid and in-person Masters' Degrees programs in Health Informatics becoming available both to recent college graduates and established professionals."James B. Couch, M.D., J.D., FACPEInterim Director, M.S. in Health Administration Degree ProgramFordham University"True wellness innovation requires the recruitment of multi-disciplinary participants. This book breaks the mold with examples from healthcare and other professionals who have leveraged informatics to better the lives of their constituents."Jason Helgerson, Founder & CEO, Helgerson Solutions Group LLC"I am saying nothing new when I say, "healthcare is complicated". Dr. Salvatore Volpe has assembled a team of many of America’s best-versed experts from a variety of disciplines and made complex, technical issues of today’s healthcare easy to understand. Not only informative, but a road map for developing best of class healthcare practices. A must read of healthcare leaders, present and future."Russ JonesExecutive AdvisorFelix Global"Whether for management of a global pandemic at the population level or treating individual patients in a high stake, fast-paced emergency department, the urgent imperative for better collection, analysis, and availability of actionable health data is abundantly clear. Through this valuable text, Dr. Volpe and his co-authors empower healthcare professionals to be catalysts and leaders equipped to create the robust, reliable, and interoperable health informatics processes and tools so urgently needed by patients, clinicians, and policymakers."Steven J. Stack, MD, MBA, FACEP"An interprofessional owner’s manual on Health Informatics for all health care providers! Educators must embrace the notion that the future of health care lies in encouraging technology and innovations and this book will benefit future nursing professionals to be practice ready when they graduate. Just what we need in higher education."Patricia A. Tooker, RN, DNPDean, Evelyn L. Spiro School of NursingWagner College"Information technology (IT) has revolutionized healthcare over the last decade and promises to transform healthcare for the foreseeable future. How can we harness an IT-enabled approach to address future health care challenges? How can IT be leveraged to prevent the next pandemic and for surveillance of other epidemics? How will IT rectify the inequities already present in the healthcare system? These are the questions at the core of this remarkable book. Health Informatics is required reading for anyone who plans on changing the future of healthcare. A must read for everyone!"Angelo Volandes, MD, President, ACP Decisions; Faculty, Harvard Medical School and Massachusetts General HospitalAretha Delight Davis, MD, JD, ACP Decisions, Co-Founder/Chief Executive Officer"Dr. Volpe makes an inspiring case for combining the principles of computer and information science with life sciences research, health professions, education, public health and patient care by recruiting a broad network of contributors to the field of Health Information Technologies. This book is a mind expander. Health Informatics will make you think differently about the future of healthcare and how multidisciplinary teams come together to help those in need."Aiyemobisi Williams, Co-founder, Massive Change Network and Co-host and creator of Health2049, a podcast about the future of health. "Advances in health information technology (IT) have impacted the healthcare stakeholders, especially during the COVID-19 pandemic. This book is a must-read for healthcare leaders who are helping endorse the development of cutting-edge health IT and integrating it into clinical practice! The book brings into focus strategic health IT opportunities for care improvements, enhancement of preventative care, optimization of patient care quality and outcomes, reduction of cost, and maintenance of provider and patient satisfaction, and more. It is a fantastic resource for current and future healthcare professionals!"Aleksandra Zagorin, DNP, MA, AGPCNP-BC, RNMaimonides Medical Center Department of Medicine and GeriatricsClinical Advisor and Scholar NYU Hartford Institute for Geriatric NursingDirector of Undergraduate Studies and Associate ProfessorEvelyn L. Spiro School of Nursing, Wagner College"Thank you, Dr. Volpe and co-authors for investing in this multi-disciplinary book that sheds a bright light on the opportunity and challenges of health informatics. Managed care organizations, health care delivery systems and community health workers can all benefit from understanding the new world of shared decision making, digital connection and use of data to drive meaningful insights and findings, while protecting patient privacy and promoting equity."Susan Beane, MD FACPExecutive Medical DirectorHealthfirst Partnerships – Medical Outcomes"Dr. Volpe is highly regarded not only for his extensive expertise working at the intersection of clinical care and informatics, but also as a student of the art and science of the field - an expert who readily identifies and learns from the insights of leaders across disciplines who are making change, every day. The result is this uniquely valuable compendium that will serve as the go-to resource for those seeking to understand all aspects health informatics to make care better, more efficient, and more effective."Amy Boutwell, MD, MPP, Founder and President, Collaborative Healthcare Strategies Table of ContentsChapter 1: The Value of Health IT – Nancy C. Beale, MSN, RN-BCChapter 2: Personal Health Engagement – Jan Oldenburg, FHIMSSChapter 3: Fostering Innovation in Health IT – Anuj Desai, MBAChapter 4: Ambulatory Systems: Electronic Health Records – Curtis L. Cole, MD, Adam D. Cheriff, MD, J. Travis Gossey, MD, MS, MPH, Sameer Malhotra, MD, MA, and Daniel M. Stein, MD, PhDChapter 5: Clinical Decision Support System – Parag Mehta, MD, FACPChapter 6: Medication Errors – J. Barmecha, MD, MPH, SFHM, FACPChapter 7: Racing against the Clock, Winning Back Time Spent in EHR – Parag Mehta, MD, FACPChapter 8: Hospital Systems: History and Rationale for Hospital Health IT – Virginia Lorenzi, MS, CPHIMS Chapter 9: Artificial Intelligence and Hospital Automation – Daniel J. Barchi, MEMChapter 10: Clinical and Business Intelligence – Ray Hess, MSA, RRT, FHIMSSChapter 11: Promoting Interoperability and Quality Payment Programs: The Evolving Paths of Meaningful Use – Anantachai (Tony) Panjamapirom, PhD, MBA, CPHIMS, Naomi Levinthal, MA, MS, CPHIMS, Ye Hoffman, MS, CPHIMChapter 12: Telebehavioral Health: Mental Health Landscape – Teresa Rufin, MPH, David Mou, MD, Thomas Tsang, MDChapter 13: Optimizing Medication Use through Health Information Technology: A Pharmacist’s Perspective – Troy Trygstad, PharmD, MBA, PhD; Mary Ann Kliethermes, B.S., Phar., Pharm D., FAPha, FCIOM; Anne Burns B.S. Pharm, RPh; Mary Roth McClurg, PharmD, MHS; Marie Smith, PharmD, FNAP; Jon Easter, BSPharm, RPhChapter 14: Nursing Informatics Today and Future Perspectives for Healthcare – Victoria L. Tiase, PhD, RN-BC and Whende M. Carroll, MSN, RN-BCChapter 15: Health Information Exchange: An Overview and New York State’s Model – Valerie Grey. M.A. and Nathan Donnelly, M.S. Chapter 16: Direct Interoperability Enhancing Transitions Across the Spectrum of Healthcare – Holly Miller, MD, MBA, FHIMSSChapter 17: Privacy and Security – Keith Richard Weiner, PhD, RN-BCChapter 18: Blockchain Primer – Paul Quigley, MBAChapter 19: IoT Is Watching You – Salvatore G. Volpe, MA; Paul Quigley, MBA Chapter 20: Case Study: New York City Department of Health and Mental Hygiene: Uses of Public Health Informatics in Response to COVID-19 Chapter 21: Genomic Informatics in Healthcare System – Chang-Hui Shen, PHDChapter 22: Managed Care Organizations Leverage Health Information from Multiple Sources to Drive Value – Michael Renzi, DO and Owen Moss, MPHChapter 23: Workforce Application of Informatics to Target Initiatives – William D. Myhre, MPAChapter 24: Patient-Centered Medical Home and Social Determinants of Health (SDoH) – Salvatore Volpe, MD FAAP, FACP ABP-CI, FHIMSS, CHCQM and Rick A. Moore, Ph.D.Chapter 25: eMOLST: Electronic System for Completing Medical Orders for Life-Sustaining Treatment – Patricia Bomba, M.D., M.A.C.P., F.R.C.P. and Katie Orem, M.P.H.Chapter 26: Medical Liability Insurance Data Analytics: An Opportunity to Identify Risks, Target Interventions, and Impact Policy – Thomas R. Gray, ESQ.Chapter 27: Medical-Legal: Attorney’s Perspective – Joshua R. Cohen, J.D.Chapter 28: Telehealth – Salvatore Volpe, MD, FAAP, FACP ABP-CI, FHIMSS, CHCQMChapter 29: Future Possibilities– Salvatore Volpe, MDChapter 29: Future Possibilities – Salvatore Volpe
£65.54
John Wiley & Sons Inc Health Information Management
Book SynopsisThe Updated and Extensively Revised Guide to Developing Efficient Health Information Management Systems Health Information Management is the most comprehensive introduction to the study and development of health information management (HIM). Students in all areas of health care gain an unmatched understanding of the entire HIM profession and how it currently relates to the complex and continuously evolving field of health care in the United States. This brand-new Sixth Edition represents the most thorough revision to date of this cornerstone resource. Inside, a group of hand-picked HIM educators and practitioners representing the vanguard of the field provide fundamental guidelines on content and structure, analysis, assessment, and enhanced information. Fully modernized to reflect recent changes in the theory and practice of HIM, this latest edition features all-new illustrative examples and in-depth case studies, along with: Fresh anTable of ContentsAbout the Editor viiAbout the Contributors ixPreface xvAcknowledgments xvii 1 Health Information Management and the Healthcare Institution 1Felecia Williams 2 Health Record Content and Structure of the Health Record 25Linda Galocy 3 The Health Record: Electronic and Paper 55Linda Galocy 4 Healthcare Topics in Data Governance and Data Management 81Dilhari R. DeAlmeida and Suzanne Paone 5 Health Law, Data Privacy and Security, Fraud, and Abuse 105Dorinda M. Sattler 6 Informatics, Analytics, Data Use, and System Support 143Dorinda M. Sattler 7 Coding, Compliance, and Classification Systems 171Sandra K. Rains, Margaret A. Skurka, and Margie White 8 Clinical Documentation Improvement 205Sandra K. Rains 9 Revenue Cycle and Reimbursement 227Karen Wright 10 Strategic, Financial, and Organizational Management 253Janelle Wapola and Katie Kerr Index 283
£76.46
John Wiley & Sons Inc Applied Smart Health Care Informatics
Book SynopsisApplied Smart Health Care Informatics Explores how intelligent systems offer new opportunities for optimizing the acquisition, storage, retrieval, and use of information in healthcare Applied Smart Health Care Informatics explores how health information technology and intelligent systems can be integrated and deployed to enhance healthcare management. Edited and authored by leading experts in the field, this timely volume introduces modern approaches for managing existing data in the healthcare sector by utilizing artificial intelligence (AI), meta-heuristic algorithms, deep learning, the Internet of Things (IoT), and other smart technologies. Detailed chapters review advances in areas including machine learning, computer vision, and soft computing techniques, and discuss various applications of healthcare management systems such as medical imaging, electronic medical records (EMR), and drug development assistance. Throughout the text, the authors propose new reTable of ContentsPreface xiii About the Editors xix List of Contributors xxv 1 An Overview of Applied Smart Health Care Informatics in the Context of Computational Intelligence 1Sourav De and Rik Das 1.1 Introduction 1 1.2 Big Data Analytics in Healthcare 2 1.3 AI in Healthcare 3 1.4 Cloud Computing in Healthcare 4 1.5 IoT in Healthcare 4 1.6 Conclusion 5 References 5 2 A Review on Deep Learning Method for Lung Cancer Stage Classification Using PET-CT 9Kaushik Pratim Das, Chandra J, and Dr Nachamai M 2.1 Introduction 9 2.1.1 Scope of the Research 10 2.1.2 TNM Staging 11 2.1.2.1 TNM Descriptors for Staging per IASLC Guidelines 11 2.1.2.2 PET-CT Scan in Lung Cancer Imaging 12 2.2 Related Works 12 2.2.1 Artificial Intelligence in Medical Imaging 14 2.2.2 Classification for Medical Imaging 14 2.2.2.1 Deep Learning 15 2.2.2.2 Image Classification Using Deep-learning Techniques 15 2.3 Methods 15 2.3.1 Transfer Learning 15 2.3.2 AlexNet 16 2.3.3 AlexNet Architecture 16 2.3.4 Experimental Setup 17 2.3.4.1 Image Processing 18 2.3.4.2 Data Augmentation 19 2.3.4.3 Training and Validation 19 2.4 Results and Discussion 19 2.4.1 Primary Tumor (T) 19 2.4.2 Metastasis (M) 21 2.4.3 Lymph Node (N) 21 2.4.4 Classification Accuracy of AlexNet 24 2.4.5 Comparative Analysis 25 2.4.6 Limitations 26 2.5 Conclusion 26 References 27 3 Formal Methods for the Security of Medical Devices 31Srinivas Pinisetty, Nathan Allen, Hammond Pearce, Mark Trew, Manoj Singh Gaur, and Partha Roop 3.1 Introduction 31 3.1.1 Pacemaker Security 33 3.1.2 Overview 34 3.2 Background: Cardiac Pacemakers 34 3.2.1 Pacemakers 35 3.2.1.1 Operation of a DDD Mode Pacemaker 36 3.2.2 The Cardiac System 37 3.2.2.1 Electrograms and Electrocardiograms 38 3.3 State of the Art, Formal Verification Techniques 39 3.3.1 Formal Verification Techniques 40 3.3.1.1 Static Verification Techniques 41 3.3.1.2 Dynamic Verification Techniques 42 3.3.2 Runtime Verification 43 3.3.2.1 A Brief Overview of Some Runtime Verification Frameworks 44 3.3.3 Correcting Execution of a System at Runtime (Runtime Enforcement) 45 3.3.3.1 Runtime Enforcement of Untimed Properties 46 3.3.3.2 Runtime Enforcement Approaches for Timed Properties 46 3.4 Formal Runtime-Based Approaches for Medical Device Security 47 3.4.1 Overview of the Approach 47 3.4.2 Mapping EGM Properties to ECG Properties 48 3.4.3 Security of Pacemakers Using Runtime Verification 49 3.4.3.1 Timed Words, Timed Languages, and Defining Timed Properties 50 3.4.3.2 Runtime Verification Monitor 51 3.4.3.3 Architecture of the Monitoring System 53 3.4.3.4 Implementation of the ECG Processing and RV Monitor Modules 53 3.4.3.5 Summary of Experiments and Results 54 3.4.4 Securing Pacemakers with Runtime Enforcement Hardware 54 3.4.4.1 Preliminaries: Words, Languages, and Defining Properties as DTA 55 3.4.4.2 Runtime Enforcement Monitor 56 3.4.4.3 Verification of the Enforcer Hardware 58 3.4.4.4 How Does the Enforcer Prevent Security Attacks? 58 3.4.4.5 Summary of Experiments and Results 59 3.5 Summary 59 References 60 4 Integrating Two Deep Learning Models to Identify Gene Signatures in Head and Neck Cancer from Multi-Omics Data 67Suparna Saha, Sumanta Ray, and Sanghamitra Bandyopadhyay 4.1 Introduction 67 4.2 Related Work 68 4.3 Materials and Methods 70 4.3.1 A Brief Introduction of the Capsule Network 70 4.3.2 An Introduction to Autoencoders 71 4.4 Results 72 4.4.1 Data Set Details 72 4.4.1.1 Gene Expression Data (Illumina Hiseq) 72 4.4.1.2 Human Methylation 450K 73 4.4.2 Architecture of Autoencoder Model 73 4.4.3 Architecture of the Proposed Capsule Network Model 74 4.4.4 Validation of Two Deep Learning Models 75 4.4.5 Gene Signatures from Primary Capsules 76 4.5 Discussion 77 Acknowledgments 78 References 79 5 A Review of Computational Learning and IoT Applications to High-Throughput Array-Based Sequencing and Medical Imaging Data in Drug Discovery and Other Health Care Systems 83Soham Choudhuri, Saurav Mallik, Bhaswar Ghosh, Tapas Si, Tapas Bhadra, Ujjwal Maulik, and Aimin Li 5.1 Introduction 83 5.2 Biological Terms 84 5.3 Single-Cell Sequencing (scRNA-seq) Data 86 5.3.1 Computational Methods for Interpreting scRNA-seq Data 86 5.3.1.1 Visualizing and Clustering Cells 86 5.3.1.2 Inference and Branching Analysis of Cellular Trajectory 86 5.3.1.3 Identifying Highly Variable Genes 86 5.3.1.4 Identifying Marker and Differentially Expressed Genes 90 5.4 Methods of Multi-Omic Data Integration 90 5.4.1 Unsupervised Data Integration Methods 91 5.4.1.1 Matrix Factorization Methods 91 5.4.1.2 Bayesian Methods 91 5.4.1.3 Network-Based Methods 94 5.4.1.4 Multi-Step Analysis and Multiple Kernel Learning 94 5.4.2 Supervised Data Integration 95 5.4.2.1 Network-Based Methods 95 5.4.2.2 Multiple Kernel Learning 95 5.4.2.3 Multi-Step Analysis 95 5.4.3 Semi-Supervised Data Integration 95 5.4.3.1 GeneticInterPred 97 5.5 AI Drug Discovery 97 5.5.1 AI Primary Drug Screening 97 5.5.1.1 Cell Sorting and Classification with Image Analysis 97 5.5.2 AI Secondary Drug Screening 99 5.5.2.1 Physical Properties Predictions 99 5.5.2.2 Predictions of Bio-Activity 99 5.5.2.3 Prediction of Toxicity 99 5.5.3 AI in Drug Design 99 5.5.3.1 Prediction of Target Protein 3D Structures 99 5.5.3.2 Predicting Drug-Protein Interactions 100 5.5.4 Planning Chemical Synthesis with AI 100 5.5.4.1 Retro-Synthesis Pathway Prediction 100 5.5.4.2 Reaction Yield Predictions and Reaction Mechanism Insights 100 5.6 Medical Imaging Data Analysis 100 5.6.1 Analysis: Radio-Mic Quantification 101 5.6.2 Analysis: Bio-Marker Identification 101 5.7 Applying IoT (Internet of Things) to Biomedical Research 102 5.7.1 IoT and IoMT Applications for Healthcare and Well-Being 102 5.7.1.1 Wireless Medical Devices 102 5.8 Conclusions 102 Acknowledgments 102 References 102 6 Association Rule Mining Based on Ethnic Groups and Classification using Super Learning 111Md Faisal Kabir and Simone A. Ludwig 6.1 Introduction 111 6.2 Background 112 6.3 Motivation and Contribution 114 6.4 Data Analysis 115 6.4.1 Data Description 115 6.4.2 Data Preprocessing 115 6.4.3 Further Preprocessing for Ethnic Group Rule Discovery with Multiple Consequences 115 6.4.3.1 Transaction-Like Database for Association Rule 115 6.4.4 Classification Data Set 116 6.5 Methodology 117 6.5.1 Association Rule Mining 117 6.5.2 Super Learning 118 6.5.2.1 Ensemble or Super Learner Set-Up 118 6.6 Experiments and Results 119 6.6.1 Rules Discovery 120 6.6.1.1 Rules of Breast Cancer Patients Based on Ethnic Groups 120 6.6.1.2 Interpreting Rules 120 6.6.2 Evaluation Criteria of Classification Model 121 6.6.2.1 Super Learner Results 124 6.6.3 Discussion 125 6.7 Conclusion and Future Work 126 References 127 7 Neuro-Rough Hybridization for Recognition of Virus Particles from TEM Images 131Debamita Kumar and Pradipta Maji 7.1 Introduction 131 7.2 Existing Approaches for Virus Particle Classification 132 7.3 Proposed Algorithm 134 7.3.1 Extraction of Local Textural Features 135 7.3.2 Selection of Class-Pair Relevant Features 135 7.3.3 Extraction of Discriminating Features 138 7.3.4 Classification 139 7.4 Experimental Results and Discussion 140 7.4.1 Experimental Setup 140 7.4.2 Methods Compared 140 7.4.3 Database Considered 141 7.4.4 Effectiveness of Proposed Approach 141 7.4.5 Comparative Performance Analysis 143 7.4.5.1 Comparison with Deep Architectures 144 7.4.5.2 Comparison with Existing Approaches 145 7.5 Conclusion 146 References 147 8 Neural Network Optimizers for Brain Tumor Image Detection 151T. Kalaiselvi and S.T. Padmapriya 8.1 Introduction 151 8.2 Related Works 152 8.3 Background 153 8.3.1 Types of Neural Networks 153 8.3.2 Tunable Elements of Neural Networks 154 8.3.2.1 Basic Parameters 154 8.3.2.2 Hyperparameters 154 8.3.2.3 Regularization Techniques 155 8.3.2.4 Neural Network Optimizers 156 8.4 Case Study - Brain Tumor Detection 157 8.4.1 Methodology 157 8.4.2 Data Sets and Metrics 157 8.4.3 Results and Discussion 159 8.5 Conclusion 162 References 162 9 Abnormal Slice Classification from MRI Volumes using the Bilateral Symmetry of Human Head Scans 165N. Kalaichelvi, T. Kalaiselvi, and K. Somasundaram 9.1 Introduction 165 9.1.1 MRIs of the Human Brain 165 9.1.2 Normal and Abnormal Slices 166 9.1.3 Background 167 9.1.3.1 Decision Tree Classifiers 167 9.1.3.2 K-Nearest Neighbours (KNN) Classifiers 168 9.1.3.3 Support Vector Machine (SVM) 168 9.1.3.4 Naive Bayes 169 9.1.3.5 Artificial Neural Network (ANN) 169 9.1.3.6 Back-Propagation Neural Network (BPN) 170 9.1.3.7 Random Forest Classifiers 170 9.2 Literature Review 171 9.3 Methodology 172 9.3.1 Preprocessing 173 9.3.2 Feature Extraction 174 9.3.3 Feature Selection 175 9.3.4 Classification 177 9.3.5 Cross-Validation 177 9.3.6 Training Validation and Testing 178 9.4 Materials and Metrics 179 9.4.1 Confusion Matrix 179 9.5 Results and Discussion 180 9.6 Conclusion 182 References 183 10 Conclusion 187Siddhartha Bhattacharyya References 188 Index 191
£94.46
John Wiley & Sons Inc Cognitive Intelligence and Big Data in Healthcare
Book SynopsisCOGNITIVE INTELLIGENCE AND BIG DATA IN HEALTHCARE Applications of cognitive intelligence, advanced communication, and computational methods can drive healthcare research and enhance existing traditional methods in disease detection and management and prevention. As health is the foremost factor affecting the quality of human life, it is necessary to understand how the human body is functioning by processing health data obtained from various sources more quickly. Since an enormous amount of data is generated during data processing, a cognitive computing system could be applied to respond to queries, thereby assisting in customizing intelligent recommendations. This decision-making process could be improved by the deployment of cognitive computing techniques in healthcare, allowing for cutting-edge techniques to be integrated into healthcare to provide intelligent services in various healthcare applications. This book tackles all these issues and provides insight into these diversifieTable of ContentsPreface xv 1 Era of Computational Cognitive Techniques in Healthcare Systems 1Deependra Rastogi, Varun Tiwari, Shobhit Kumar and Prabhat Chandra Gupta 1.1 Introduction 2 1.2 Cognitive Science 3 1.3 Gap Between Classical Theory of Cognition 4 1.4 Cognitive Computing’s Evolution 6 1.5 The Coming Era of Cognitive Computing 7 1.6 Cognitive Computing Architecture 9 1.6.1 The Internet-of-Things and Cognitive Computing 10 1.6.2 Big Data and Cognitive Computing 11 1.6.3 Cognitive Computing and Cloud Computing 13 1.7 Enabling Technologies in Cognitive Computing 13 1.7.1 Reinforcement Learning and Cognitive Computing 13 1.7.2 Cognitive Computing with Deep Learning 15 1.7.2.1 Relational Technique and Perceptual Technique 15 1.7.2.2 Cognitive Computing and Image Understanding 16 1.8 Intelligent Systems in Healthcare 17 1.8.1 Intelligent Cognitive System in Healthcare (Why and How) 20 1.9 The Cognitive Challenge 32 1.9.1 Case Study: Patient Evacuation 32 1.9.2 Case Study: Anesthesiology 32 1.10 Conclusion 34 References 35 2 Proposal of a Metaheuristic Algorithm of Cognitive Computing for Classification of Erythrocytes and Leukocytes in Healthcare Informatics 41Ana Carolina Borges Monteiro, Reinaldo Padilha França, Rangel Arthur and Yuzo Iano 2.1 Introduction 42 2.2 Literature Concept 44 2.2.1 Cognitive Computing Concept 44 2.2.2 Neural Networks Concepts 47 2.2.3 Convolutional Neural Network 49 2.2.4 Deep Learning 52 2.3 Materials and Methods (Metaheuristic Algorithm Proposal) 55 2.4 Case Study and Discussion 57 2.5 Conclusions with Future Research Scopes 60 References 61 3 Convergence of Big Data and Cognitive Computing in Healthcare 67R. Sathiyaraj, U. Rahamathunnisa, M.V. Jagannatha Reddy and T. Parameswaran 3.1 Introduction 68 3.2 Literature Review 70 3.2.1 Role of Cognitive Computing in Healthcare Applications 70 3.2.2 Research Problem Study by IBM 73 3.2.3 Purpose of Big Data in Healthcare 74 3.2.4 Convergence of Big Data with Cognitive Computing 74 3.2.4.1 Smart Healthcare 74 3.2.4.2 Big Data and Cognitive Computing-Based Smart Healthcare 75 3.3 Using Cognitive Computing and Big Data, a Smart Healthcare Framework for EEG Pathology Detection and Classification 76 3.3.1 EEG Pathology Diagnoses 76 3.3.2 Cognitive–Big Data-Based Smart Healthcare 77 3.3.3 System Architecture 79 3.3.4 Detection and Classification of Pathology 80 3.3.4.1 EEG Preprocessing and Illustration 80 3.3.4.2 CNN Model 80 3.3.5 Case Study 81 3.4 An Approach to Predict Heart Disease Using Integrated Big Data and Cognitive Computing in Cloud 83 3.4.1 Cloud Computing with Big Data in Healthcare 86 3.4.2 Heart Diseases 87 3.4.3 Healthcare Big Data Techniques 88 3.4.3.1 Rule Set Classifiers 88 3.4.3.2 Neuro Fuzzy Classifiers 89 3.4.3.3 Experimental Results 91 3.5 Conclusion 92 References 93 4 IoT for Health, Safety, Well-Being, Inclusion, and Active Aging 97R. Indrakumari, Nilanjana Pradhan, Shrddha Sagar and Kiran Singh 4.1 Introduction 98 4.2 The Role of Technology in an Aging Society 99 4.3 Literature Survey 100 4.4 Health Monitoring 101 4.5 Nutrition Monitoring 105 4.6 Stress-Log: An IoT-Based Smart Monitoring System 106 4.7 Active Aging 108 4.8 Localization 108 4.9 Navigation Care 111 4.10 Fall Monitoring 113 4.10.1 Fall Detection System Architecture 114 4.10.2 Wearable Device 114 4.10.3 Wireless Communication Network 114 4.10.4 Smart IoT Gateway 115 4.10.5 Interoperability 115 4.10.6 Transformation of Data 115 4.10.7 Analyzer for Big Data 115 4.11 Conclusion 115 References 116 5 Influence of Cognitive Computing in Healthcare Applications 121Lucia Agnes Beena T. and Vinolyn Vijaykumar 5.1 Introduction 122 5.2 Bond Between Big Data and Cognitive Computing 124 5.3 Need for Cognitive Computing in Healthcare 126 5.4 Conceptual Model Linking Big Data and Cognitive Computing 128 5.4.1 Significance of Big Data 128 5.4.2 The Need for Cognitive Computing 129 5.4.3 The Association Between the Big Data and Cognitive Computing 130 5.4.4 The Advent of Cognition in Healthcare 132 5.5 IBM’s Watson and Cognitive Computing 133 5.5.1 Industrial Revolution with Watson 134 5.5.2 The IBM’s Cognitive Computing Endeavour in Healthcare 135 5.6 Future Directions 137 5.6.1 Retail 138 5.6.2 Research 139 5.6.3 Travel 139 5.6.4 Security and Threat Detection 139 5.6.5 Cognitive Training Tools 140 5.7 Conclusion 141 References 141 6 An Overview of the Computational Cognitive from a Modern Perspective, Its Techniques and Application Potential in Healthcare Systems 145Reinaldo Padilha França, Ana Carolina Borges Monteiro, Rangel Arthur and Yuzo Iano 6.1 Introduction 146 6.2 Literature Concept 148 6.2.1 Cognitive Computing Concept 148 6.2.1.1 Application Potential 151 6.2.2 Cognitive Computing in Healthcare 153 6.2.3 Deep Learning in Healthcare 157 6.2.4 Natural Language Processing in Healthcare 160 6.3 Discussion 162 6.4 Trends 163 6.5 Conclusions 164 References 165 7 Protecting Patient Data with 2F- Authentication 169G. S. Pradeep Ghantasala, Anu Radha Reddy and R. Mohan Krishna Ayyappa 7.1 Introduction 170 7.2 Literature Survey 175 7.3 Two-Factor Authentication 177 7.3.1 Novel Features of Two-Factor Authentication 178 7.3.2 Two-Factor Authentication Sorgen 178 7.3.3 Two-Factor Security Libraries 179 7.3.4 Challenges for Fitness Concern 180 7.4 Proposed Methodology 181 7.5 Medical Treatment and the Preservation of Records 186 7.5.1 Remote Method of Control 187 7.5.2 Enabling Healthcare System Technology 187 7.6 Conclusion 189 References 190 8 Data Analytics for Healthcare Monitoring and Inferencing 197Gend Lal Prajapati, Rachana Raghuwanshi and Rambabu Raghuwanshi 8.1 An Overview of Healthcare Systems 198 8.2 Need of Healthcare Systems 198 8.3 Basic Principle of Healthcare Systems 199 8.4 Design and Recommended Structure of Healthcare Systems 199 8.4.1 Healthcare System Designs on the Basis of these Parameters 200 8.4.2 Details of Healthcare Organizational Structure 201 8.5 Various Challenges in Conventional Existing Healthcare System 202 8.6 Health Informatics 202 8.7 Information Technology Use in Healthcare Systems 203 8.8 Details of Various Information Technology Application Use in Healthcare Systems 203 8.9 Healthcare Information Technology Makes it Possible to Manage Patient Care and Exchange of Health Information Data, Details are Given Below 204 8.10 Barriers and Challenges to Implementation of Information Technology in Healthcare Systems 205 8.11 Healthcare Data Analytics 206 8.12 Healthcare as a Concept 206 8.13 Healthcare’s Key Technologies 207 8.14 The Present State of Smart Healthcare Application 207 8.15 Data Analytics with Machine Learning Use in Healthcare Systems 208 8.16 Benefit of Data Analytics in Healthcare System 210 8.17 Data Analysis and Visualization: COVID-19 Case Study in India 210 8.18 Bioinformatics Data Analytics 222 8.18.1 Notion of Bioinformatics 222 8.18.2 Bioinformatics Data Challenges 222 8.18.3 Sequence Analysis 222 8.18.4 Applications 223 8.18.5 COVID-19: A Bioinformatics Approach 224 8.19 Conclusion 224 References 225 9 Features Optimistic Approach for the Detection of Parkinson’s Disease 229R. Shantha Selva Kumari, L. Vaishalee and P. Malavikha 9.1 Introduction 230 9.1.1 Parkinson’s Disease 230 9.1.2 Spect Scan 231 9.2 Literature Survey 232 9.3 Methods and Materials 233 9.3.1 Database Details 233 9.3.2 Procedure 234 9.3.3 Pre-Processing Done by PPMI 235 9.3.4 Image Analysis and Features Extraction 235 9.3.4.1 Image Slicing 235 9.3.4.2 Intensity Normalization 237 9.3.4.3 Image Segmentation 239 9.3.4.4 Shape Features Extraction 240 9.3.4.5 SBR Features 241 9.3.4.6 Feature Set Analysis 242 9.3.4.7 Surface Fitting 242 9.3.5 Classification Modeling 243 9.3.6 Feature Importance Estimation 246 9.3.6.1 Need for Analysis of Important Features 246 9.3.6.2 Random Forest 247 9.4 Results and Discussion 248 9.4.1 Segmentation 248 9.4.2 Shape Analysis 249 9.4.3 Classification 249 9.5 Conclusion 252 References 253 10 Big Data Analytics in Healthcare 257Akanksha Sharma, Rishabha Malviya and Ramji Gupta 10.1 Introduction 258 10.2 Need for Big Data Analytics 260 10.3 Characteristics of Big Data 264 10.3.1 Volume 264 10.3.2 Velocity 265 10.3.3 Variety 265 10.3.4 Veracity 265 10.3.5 Value 265 10.3.6 Validity 265 10.3.7 Variability 266 10.3.8 Viscosity 266 10.3.9 Virality 266 10.3.10 Visualization 266 10.4 Big Data Analysis in Disease Treatment and Management 267 10.4.1 For Diabetes 267 10.4.2 For Heart Disease 268 10.4.3 For Chronic Disease 270 10.4.4 For Neurological Disease 271 10.4.5 For Personalized Medicine 271 10.5 Big Data: Databases and Platforms in Healthcare 279 10.6 Importance of Big Data in Healthcare 285 10.6.1 Evidence-Based Care 285 10.6.2 Reduced Cost of Healthcare 285 10.6.3 Increases the Participation of Patients in the Care Process 285 10.6.4 The Implication in Health Surveillance 285 10.6.5 Reduces Mortality Rate 285 10.6.6 Increase of Communication Between Patients and Healthcare Providers 286 10.6.7 Early Detection of Fraud and Security Threats in Health Management 286 10.6.8 Improvement in the Care Quality 286 10.7 Application of Big Data Analytics 286 10.7.1 Image Processing 286 10.7.2 Signal Processing 287 10.7.3 Genomics 288 10.7.4 Bioinformatics Applications 289 10.7.5 Clinical Informatics Application 291 10.8 Conclusion 293 References 294 11 Case Studies of Cognitive Computing in Healthcare Systems: Disease Prediction, Genomics Studies, Medical Image Analysis, Patient Care, Medical Diagnostics, Drug Discovery 303V. Sathananthavathi and G. Indumathi 11.1 Introduction 304 11.1.1 Glaucoma 304 11.2 Literature Survey 306 11.3 Methodology 309 11.3.1 Sclera Segmentation 310 11.3.1.1 Fully Convolutional Network 311 11.3.2 Pupil/Iris Ratio 313 11.3.2.1 Canny Edge Detection 314 11.3.2.2 Mean Redness Level (MRL) 315 11.3.2.3 Red Area Percentage (RAP) 316 11.4 Results and Discussion 317 11.4.1 Feature Extraction from Frontal Eye Images 318 11.4.1.1 Level of Mean Redness (MRL) 318 11.4.1.2 Percentage of Red Area (RAP) 318 11.4.2 Images of the Frontal Eye Pupil/Iris Ratio 318 11.4.2.1 Histogram Equalization 319 11.4.2.2 Morphological Reconstruction 319 11.4.2.3 Canny Edge Detection 319 11.4.2.4 Adaptive Thresholding 320 11.4.2.5 Circular Hough Transform 321 11.4.2.6 Classification 322 11.5 Conclusion and Future Work 324 References 325 12 State of Mental Health and Social Media: Analysis, Challenges, Advancements 327Atul Pankaj Patil, Kusum Lata Jain, Smaranika Mohapatra and Suyesha Singh 12.1 Introduction 328 12.2 Introduction to Big Data and Data Mining 328 12.3 Role of Sentimental Analysis in the Healthcare Sector 330 12.4 Case Study: Analyzing Mental Health 332 12.4.1 Problem Statement 332 12.4.2 Research Objectives 333 12.4.3 Methodology and Framework 333 12.4.3.1 Big 5 Personality Model 333 12.4.3.2 Openness to Explore 334 12.4.3.3 Methodology 335 12.4.3.4 Detailed Design Methodologies 340 12.4.3.5 Work Done Details as Required 341 12.5 Results and Discussion 343 12.6 Conclusion and Future 345 References 346 13 Applications of Artificial Intelligence, Blockchain, and Internet-of-Things in Management of Chronic Disease 349Geetanjali, Rishabha Malviya, Rajendra Awasthi, Pramod Kumar Sharma, Nidhi Kala, Vinod Kumar and Sanjay Kumar Yadav 13.1 Introduction 350 13.2 Artificial Intelligence and Management of Chronic Diseases 351 13.3 Blockchain and Healthcare 354 13.3.1 Blockchain and Healthcare Management of Chronic Disease 355 13.4 Internet-of-Things and Healthcare Management of Chronic Disease 358 13.5 Conclusions 360 References 360 14 Research Challenges and Future Directions in Applying Cognitive Computing in the Healthcare Domain 367BKSP Kumar Raju Alluri 14.1 Introduction 367 14.2 Cognitive Computing Framework in Healthcare 371 14.3 Benefits of Using Cognitive Computing for Healthcare 372 14.4 Applications of Deploying Cognitive Assisted Technology in Healthcare Management 374 14.4.1 Using Cognitive Services for a Patient’s Healthcare Management 375 14.4.2 Using Cognitive Services for Healthcare Providers 376 14.5 Challenges in Using the Cognitive Assistive Technology in Healthcare Management 377 14.6 Future Directions for Extending Heathcare Services Using CATs 380 14.7 Addressing CAT Challenges in Healthcare as a General Framework 384 14.8 Conclusion 384 References 385 Index 391
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