Medical equipment, devices and techniques Books

Book SynopsisUsing examples drawn from biomedicine and biomedical engineering, this essential reference book brings you comprehensive coverage of all the major techniques currently available to build computer-assisted decision support systems. You will find practical solutions for biomedicine based on current theory and applications of neural networks, artificial intelligence, and other methods for the development of decision aids, including hybrid systems. Neural Networks and Artificial Intelligence for Biomedical Engineering offers students and scientists of biomedical engineering, biomedical informatics, and medical artificial intelligence a deeper understanding of the powerful techniques now in use with a wide range of biomedical applications. Highlighted topics include: Types of neural networks and neural network algorithms Knowledge representation, knowledge acquisition, and reasoning methodologies Chaotic analysis of biomedical time series Table of ContentsPreface. Acknowledgments. Overview. NEURAL NETWORKS. Foundations of Neural Networks. Classes of Neural Networks. Classification Networks and Learning. Supervised Learning. Unsupervised Learning. Design Issues. Comparative Analysis. Validation and Evaluation. ARTIFICIAL INTELLIGENCE. Foundation of Computer-Assisted Decision Making. Knowledge Representation. Knowledge Acquisition. Reasoning Methodologies. Validation and Evaluation. ALTERNATIVE APPROACHES. Genetic Algorithms. Probabilistic Systems. Fuzzy Systems. Hybrid Systems. HyperMerge, a Hybird Expert System. Future Perspectives. Index. About the Authors.

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Book SynopsisOffers professional and executive-level insight into trends and potential technological advances in the field of medicine. This book covers topics ranging from: fundamental advances in computing and administration, research, nursing, and patient care delivery to non-invasive surgery, bio-molecular therapies, bionics, and more.Table of ContentsAbout the Authors v About the References and Notes ix Acknowledgments xi Introduction xiii Part 1 Trends in Technology Chapter 1 The Rate of Change 3 Chapter 2 Fundamental Trends in Technology 17 Chapter 3 Trends in Administration and Control 43 Chapter 4 Advances in Research Methods 69 Chapter 5 Emerging Products and Services 97 Chapter 6 Androids and Cyborgs 121 Chapter 7 Preparing for the Future 139 Part 2 Professional Perspectives Chapter 8 The Process of the Health Care Encounter 155 Chapter 9 Impact of Technology on Nursing Care 181 Chapter 10 Hospitals and the Forces of Change 193 Chapter 11 A Payer's Perspective on the Future 209 Chapter 12 Leadership, Followship, and Science 231 Chapter 13 Epilogue: A Postscript on Progress 251 Index 255

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Book SynopsisIn a concluding chapter he applies the book's historical insights to medical practice today-asking why, for example, modern diagnostic tests have not been used to give doctors more time to spend with patients.Trade Review[Howell's] early twentieth-century portrait is fresh and important, as an analysis of medical practice just coming to grips with the technological world. Nature I recommend this delightful book to anyone interested in the history of medicine. -- Seymour Perry New England Journal of Medicine

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Book SynopsisIntimate epistolary exchanges between Cabot and his patients shed light on the challenges presented by the new technologies-especially their impact on the personal relationships between doctor and patient-providing insight into a time of expanding science and radical change.Trade ReviewA fine book, an engaging example of the best sort of contemporary history... Crenner has provided as much material for the historian as for the historically minded physician... rigorously researched and fascinating. -- Richard Barnett The Lancet 2005 An important reference for readers who are interested in the intellectual and organizational contributions of Richard Cabot... of interest to all who would enjoy an elegant look back at the pathways by which modern medicine has developed. -- Dwight K. Oxley, MD Archives of Pathology and Laboratory Medicine 2006 An informative book. -- Ian Cameron Canadian Family Physician 2006 Private Practice is solid scholarship, a model for students of medical history, a significant contribution for medical historians, and an inspiration for further research. Journal of the History of Medicine and Allied Sciences 2006 An important book, thoroughly researched and documented... Readers interested in the sociology of medicine will find that Cabot's private practice yields new insights. -- David Faflik New England Quarterly 2007Table of ContentsPrefaceAcknowledgementsChapter 1. The Authority of a Scientific DoctorChapter 2. Organizing a Private Office: Between Home and HospitalChapter 3. The Diagnosis of Hidden DiseaseChapter 4. Treatment: How to Know What WorksChapter 5. Nervous Disease and Personal IdentityChapter 6. Medical Care for the Dying, in Principle and in FactChapter 7. From Cabot's Day to Ours: Ideals of the Medical RelationshipNotesIndex

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Book SynopsisA portable study guide for MLS & MLT exams. More than 600 cards concisely summarize common procedures and disorders, critical knowledge for entry-level practice, and cover topics that are frequently included on MLS and MLT certification exams.Table of Contents I.Laboratory Operations, Management, and Education II.Clinical Chemistry III.Clinical Microbiology IV.Hematology V.Immunology VI.Immunohematology VII.Urinalysis and Body Fluids VIII.Molecular Diagnostics

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Book SynopsisBiomedical nanotechnology is one of the fastest-growing fields of research across the globe. However, even the most promising technologies may never realize their full potential if public and political opinions are galvanized against them, a situation clearly evident in such controversial fields as cloning and stem cell research. Biomedical Nanotechnology presents state-of-the-art research in the field and also considers the socio-political risks and perceptions of this important science.Contributed by prominent experts in this expansive and interdisciplinary field, Biomedical Nanotechnology examines developments in three sub-fields: nanodrugs and drug delivery; prostheses and implants; and diagnostics and screening technologies. The authors compare new capabilities introduced by nanotechnology to traditional methods of release, target, and controlled drug delivery in the body. They also consider the challenge of understanding and controlling the biological proTable of ContentsIntroduction: Converging Technologies: Nanotechnology and Biomedicine. Trends in Biomedical Nanotechnology Programs Worldwide. Nanotechnology and Trends in Drug Delivery Systems with Self-Assembled Carriers. Implants and Prostheses. Diagnostics and High Throughput Screening. Nano-Enabled Components and Systems for Biodefense. Social and Economic Contexts: Making Choices in the Development of Biomedical Nanotechnology. Potential Risks and Remedies. Index.

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Book SynopsisTwo of the most important yet often overlooked aspects of a medical device are its usability and accessibility. This is important not only for health care providers, but also for older patients and users with disabilities or activity limitations. Medical Instrumentation: Accessibility and Usability Considerations focuses on how lack of usability and accessibility pose problems for designers and users of medical devices, and how to overcome these limitations. Divided into five broad sections, the book first addresses the nature and extent of the problem by identifying access barriers, human factors, and policy issues focused on the existing infrastructure. The subsequent sections examine responses to the problem, beginning with tools for usability and accessibility analysis and principles of design for medical instrumentation. Building on this foundation, the third section focuses on recommendations for design guidelines while the fourth section explores emerging trends andTable of ContentsBackground: The Problem, Existing Infrastructure, and Possible Solutions. Tools for Usability and Accessibility Analysis. Considerations in Design Guideline Development. Considerations in Emerging Trends and Technologies. Outputs of the Workshop: Key Knowledge Gaps, Barriers, Recommendations. Appendices. Glossary of Terms.

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Book SynopsisFrom its initial clinical use, over 28 years ago, to its current extensive use (over 100,000 times annually in the US alone), balloon pump equipment has developed into sophisticated, computer--assisted technology for mechanically aiding circulation.Trade Review"...well written and well organized. It should be welcome as a reference text to the libraries of multidisciplinary teams caring for cardiac patients." --Canadian Journal of Surgery "This book presents a comprehensive and up to date review of the use of the intra-aortic balloon pump (IABP) ...The sections on balloon pump equipment, consoles and catheters, and the physiology of balloon pumping are all particularly good, and perhaps should be mandatory reading for all trainees in cardiac surgery, cardiac anesthesia, invasive cardiology and clinical perfusion. "It is a worthwhile addition to the library of a busy cardiovascular critical care unit in which IABPs are used frequently, and is a good reference text for anyone who is considering research involving the IABP." --Canadian Journal of AnesthesiaTable of ContentsSection I: Assisted Circulation. 1. The Principle of Circulatory Assist. 2. Pulsatile Assist Devices and Counterpulsation. Section II: Cardiac Function and Pathophysiology of Cardiac Failure. 3. Cardiac Function and Classification Of Cardiac Failure. 4. Cardiogenic Shock. Section III: The Intra-Aortic Balloon Pump. 5. Historical Background. 6. Balloon Pump Equipment. 7. Balloon Pump Consoles and Catheters. 8. Physiology of Balloon Pumping. 9. General Criteria, Contraindications and Guidelines for Balloon Pumping. 10. Methods of Insertion and Removal of Intra-Aortic Balloon Catheter. 11. Complications of Balloon Pumping. Section IV: Management of Patients on Intra-Aortic Balloon Pump. 12. Nursing Care Of Patients on Intra-Aortic Balloon Pump. 13. Hemodynamic Monitoring, Data Acquisition and Assessment of Efficacy of Diastolic Augmentation. 14. Pharmacologic Treatment. 15. Management of Patients on Intra-Aortic Balloon Pump in Special Situations. 16. Problems With Use of Balloon Pumping. 17. Weaning from Intra-Aortic Balloon Pump Assist. 18. System Management in Patients on Intra-Aortic Balloon Pump. 19. Ancillary Measures in Care of Patients on Intra-Aortic Balloon Pump. Section V: Indications for Use of Intra-Aortic Balloon Pump. 20. An Overview. 21. Intra-Aortic Balloon Pump for Coronary Artery Disease. 22. Balloon Pumping in Cardiogenic Shock. 22. Balloon Pumping in Cardiac Surgery. 23. Miscellaneous Indications for Balloon Pumping

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Book SynopsisThere are many excellent textbooks that exist in the area of implantable devices for arrhythmia control. Few textbooks, however, provide a case study approach. Collectively, these workbooks provide an approach to problem solving an electrocardiographic interpretation for patients with permanent pacemakers and defibrillators. Volume 1 addresses patients with permanent pacemakers Volume 2 examines interactions between pacemakers and implantable defibrillators Volume 3 provides case studies of transtelephonic pacemakers electrocardiography Volume 4 provides more pacemaker and implantable defibrillator troubleshooting cases This volume takes a case-orientated approach, providing a diverse series of problems on a broad range of topics related to implantable defibrillators. The cases are divided into easy, moderate and complex according to their level of difficulty, allowing the reader to gauge their progress. This workbook is suitable for physicians, nurses, tecTrade Review"This volume (2) throughly covers the potential problems with implantable defibrillators with provocative problems combined with clear solutions." Doody's Review Service "In summary, these workbooks provide a case-oriented approach to identifying and managing both simple and more complex problems frequently encountered in patients with implantable defibrillators. These workbooks are best suited to individuals new in the fields of pacing and electrophysiology." Canadian Journal of CardiologyTable of ContentsVolume 1: Cardiac Pacing: A Case Approach. Volume 2: Implantable Defibrillators: A Case Approach. Volume 3: Transtelephonic, Electrocardiography and Troubleshooting: A Case Approach. Volume 4: ICDs and Pacemakers

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Book SynopsisEasy to understand and richly illustrated, this essential guide introduces the basics of critical care EEG, including continuous EEG monitoring, to acute care providers of all backgrounds and skill levels, enabling them to harness the full potential of this technique for the benefit of patients.

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Book SynopsisEmerging Technologies for Healthcare begins with an IoT-based solution for the automated healthcare sector which is enhanced to provide solutions with advanced deep learning techniques. The book provides feasible solutions through various machine learning approaches and applies them to disease analysis and prediction. An example of this is employing a three-dimensional matrix approach for treating chronic kidney disease, the diagnosis and prognostication of acquired demyelinating syndrome (ADS) and autism spectrum disorder, and the detection of pneumonia. In addition, it provides healthcare solutions for post COVID-19 outbreaks through various suitable approaches, Moreover, a detailed detection mechanism is discussed which is used to devise solutions for predicting personality through handwriting recognition; and novel approaches for sentiment analysis are also discussed with sufficient data and its dimensions. This book not only covers theoretical approaches and algorTable of ContentsPreface xvii Part I: Basics of Smart Healthcare 1 1 An Overview of IoT in Health Sectors 3Sheeba P. S. 1.1 Introduction 3 1.2 Influence of IoT in Healthcare Systems 6 1.2.1 Health Monitoring 6 1.2.2 Smart Hospitals 7 1.2.3 Tracking Patients 7 1.2.4 Transparent Insurance Claims 8 1.2.5 Healthier Cities 8 1.2.6 Research in Health Sector 8 1.3 Popular IoT Healthcare Devices 9 1.3.1 Hearables 9 1.3.2 Moodables 9 1.3.3 Ingestible Sensors 9 1.3.4 Computer Vision 10 1.3.5 Charting in Healthcare 10 1.4 Benefits of IoT 10 1.4.1 Reduction in Cost 10 1.4.2 Quick Diagnosis and Improved Treatment 10 1.4.3 Management of Equipment and Medicines 11 1.4.4 Error Reduction 11 1.4.5 Data Assortment and Analysis 11 1.4.6 Tracking and Alerts 11 1.4.7 Remote Medical Assistance 11 1.5 Challenges of IoT 12 1.5.1 Privacy and Data Security 12 1.5.2 Multiple Devices and Protocols Integration 12 1.5.3 Huge Data and Accuracy 12 1.5.4 Underdeveloped 12 1.5.5 Updating the Software Regularly 12 1.5.6 Global Healthcare Regulations 13 1.5.7 Cost 13 1.6 Disadvantages of IoT 13 1.6.1 Privacy 13 1.6.2 Access by Unauthorized Persons 13 1.7 Applications of IoT 13 1.7.1 Monitoring of Patients Remotely 13 1.7.2 Management of Hospital Operations 14 1.7.3 Monitoring of Glucose 14 1.7.4 Sensor Connected Inhaler 15 1.7.5 Interoperability 15 1.7.6 Connected Contact Lens 15 1.7.7 Hearing Aid 16 1.7.8 Coagulation of Blood 16 1.7.9 Depression Detection 16 1.7.10 Detection of Cancer 17 1.7.11 Monitoring Parkinson Patient 17 1.7.12 Ingestible Sensors 18 1.7.13 Surgery by Robotic Devices 18 1.7.14 Hand Sanitizing 18 1.7.15 Efficient Drug Management 19 1.7.16 Smart Sole 19 1.7.17 Body Scanning 19 1.7.18 Medical Waste Management 20 1.7.19 Monitoring the Heart Rate 20 1.7.20 Robot Nurse 20 1.8 Global Smart Healthcare Market 21 1.9 Recent Trends and Discussions 22 1.10 Conclusion 23 References 23 2 IoT-Based Solutions for Smart Healthcare 25Pankaj Jain, Sonia F Panesar, Bableen Flora Talwar and Mahesh Kumar Sah 2.1 Introduction 26 2.1.1 Process Flow of Smart Healthcare System 26 2.1.1.1 Data Source 26 2.1.1.2 Data Acquisition 27 2.1.1.3 Data Pre-Processing 27 2.1.1.4 Data Segmentation 28 2.1.1.5 Feature Extraction 28 2.1.1.6 Data Analytics 28 2.2 IoT Smart Healthcare System 29 2.2.1 System Architecture 30 2.2.1.1 Stage 1: Perception Layer 30 2.2.1.2 Stage 2: Network Layer 32 2.2.1.3 Stage 3: Data Processing Layer 32 2.2.1.4 Stage 4: Application Layer 33 2.3 Locally and Cloud-Based IoT Architecture 33 2.3.1 System Architecture 33 2.3.1.1 Body Area Network (BAN) 34 2.3.1.2 Smart Server 34 2.3.1.3 Care Unit 35 2.4 Cloud Computing 35 2.4.1 Infrastructure as a Service (IaaS) 37 2.4.2 Platform as a Service (PaaS) 37 2.4.3 Software as a Service (SaaS) 37 2.4.4 Types of Cloud Computing 37 2.4.4.1 Public Cloud 37 2.4.4.2 Private Cloud 38 2.4.4.3 Hybrid Cloud 38 2.4.4.4 Community Cloud 38 2.5 Outbreak of Arduino Board 38 2.6 Applications of Smart Healthcare System 39 2.6.1 Disease Diagnosis and Treatment 41 2.6.2 Health Risk Monitoring 42 2.6.3 Voice Assistants 42 2.6.4 Smart Hospital 42 2.6.5 Assist in Research and Development 43 2.7 Smart Wearables and Apps 43 2.8 Deep Learning in Biomedical 44 2.8.1 Deep Learning 46 2.8.2 Deep Neural Network Architecture 47 2.8.3 Deep Learning in Bioinformatic 49 2.8.4 Deep Learning in Bioimaging 49 2.8.5 Deep Learning in Medical Imaging 50 2.8.6 Deep Learning in Human-Machine Interface 53 2.8.7 Deep Learning in Health Service Management 53 2.9 Conclusion 55 References 55 3 QLattice Environment and Feyn QGraph Models—A New Perspective Toward Deep Learning 69Vinayak Bharadi 3.1 Introduction 70 3.1.1 Machine Learning Models 70 3.2 Machine Learning Model Lifecycle 71 3.2.1 Steps in Machine Learning Lifecycle 71 3.2.1.1 Data Preparation 72 3.2.1.2 Building the Machine Learning Model 72 3.2.1.3 Model Training 72 3.2.1.4 Parameter Selection 72 3.2.1.5 Transfer Learning 73 3.2.1.6 Model Verification 73 3.2.1.7 Model Deployment 74 3.2.1.8 Monitoring 74 3.3 A Model Deployment in Keras 75 3.3.1 Pima Indian Diabetes Dataset 75 3.3.2 Multi-Layered Perceptron Implementation in Keras 76 3.3.3 Multi-Layered Perceptron Implementation With Dropout and Added Noise 77 3.4 QLattice Environment 80 3.4.1 Feyn Models 80 3.4.1.1 Semantic Types 82 3.4.1.2 Interactions 83 3.4.1.3 Generating QLattice 83 3.4.2 QLattice Workflow 83 3.4.2.1 Preparing the Data 84 3.4.2.2 Connecting to QLattice 84 3.4.2.3 Generating QGraphs 84 3.4.2.4 Fitting, Sorting, and Updating QGraphs 85 3.4.2.5 Model Evaluation 86 3.5 Using QLattice Environment and QGraph Models for COVID-19 Impact Prediction 87 References 91 4 Sensitive Healthcare Data: Privacy and Security Issues and Proposed Solutions 93Abhishek Vyas, Satheesh Abimannan and Ren-Hung Hwang 4.1 Introduction 94 4.1.1 Types of Technologies Used in Healthcare Industry 94 4.1.2 Technical Differences Between Security and Privacy 95 4.1.3 HIPAA Compliance 95 4.2 Medical Sensor Networks/Medical Internet of Things/Body Area Networks/WBANs 97 4.2.1 Security and Privacy Issues in WBANs/WMSNs/WMIOTs 101 4.3 Cloud Storage and Computing on Sensitive Healthcare Data 112 4.3.1 Security and Privacy in Cloud Computing and Storage for Sensitive Healthcare Data 114 4.4 Blockchain for Security and Privacy Enhancement in Sensitive Healthcare Data 119 4.5 Artificial Intelligence, Machine Learning, and Big Data in Healthcare and Its Efficacy in Security and Privacy of Sensitive Healthcare Data 122 4.5.1 Differential Privacy for Preserving Privacy of Big Medical Healthcare Data and for Its Analytics 124 4.6 Conclusion 124 References 125 Part II: Employment of Machine Learning in Disease Detection 129 5 Diabetes Prediction Model Based on Machine Learning 131Ayush Kumar Gupta, Sourabh Yadav, Priyanka Bhartiya and Divesh Gupta 5.1 Introduction 131 5.2 Literature Review 133 5.3 Proposed Methodology 135 5.3.1 Data Accommodation 135 5.3.1.1 Data Collection 135 5.3.1.2 Data Preparation 136 5.3.2 Model Training 138 5.3.2.1 K Nearest Neighbor Classification Technique 139 5.3.2.2 Support Vector Machine 140 5.3.2.3 Random Forest Algorithm 142 5.3.2.4 Logistic Regression 144 5.3.3 Model Evaluation 145 5.3.4 User Interaction 145 5.3.4.1 User Inputs 146 5.3.4.2 Validation Using Classifier Model 146 5.3.4.3 Truth Probability 146 5.4 System Implementation 147 5.5 Conclusion 153 References 153 6 Lung Cancer Detection Using 3D CNN Based on Deep Learning 157Siddhant Panda, Vasudha Chhetri, Vikas Kumar Jaiswal and Sourabh Yadav 6.1 Introduction 157 6.2 Literature Review 159 6.3 Proposed Methodology 161 6.3.1 Data Handling 161 6.3.1.1 Data Gathering 161 6.3.1.2 Data Pre-Processing 162 6.3.2 Data Visualization and Data Split 162 6.3.2.1 Data Visualization 162 6.3.2.2 Data Split 162 6.3.3 Model Training 163 6.3.3.1 Training Neural Network 163 6.3.3.2 Model Optimization 166 6.4 Results and Discussion 168 6.4.1 Gathering and Pre-Processing of Data 169 6.4.1.1 Gathering and Handling Data 169 6.4.1.2 Pre-Processing of Data 170 6.4.2 Data Visualization 171 6.4.2.1 Resampling 173 6.4.2.2 3D Plotting Scan 173 6.4.2.3 Lung Segmentation 173 6.4.3 Training and Testing of Data in 3D Architecture 175 6.5 Conclusion 178 References 178 7 Pneumonia Detection Using CNN and ANN Based on Deep Learning Approach 181Priyanka Bhartiya, Sourabh Yadav, Ayush Gupta and Divesh Gupta 7.1 Introduction 182 7.2 Literature Review 183 7.3 Proposed Methodology 185 7.3.1 Data Gathering 185 7.3.1.1 Data Collection 185 7.3.1.2 Data Pre-Processing 186 7.3.1.3 Data Split 186 7.3.2 Model Training 187 7.3.2.1 Training of Convolutional Neural Network 189 7.3.2.2 Training of Artificial Neural Network 191 7.3.3 Model Fitting 193 7.3.3.1 Fit Generator 193 7.3.3.2 Validation of Accuracy and Loss Plot 193 7.3.3.3 Testing and Prediction 193 7.4 System Implementation 194 7.4.1 Data Gathering, Pre-Processing, and Split 194 7.4.1.1 Data Gathering 194 7.4.1.2 Data Pre-Processing 195 7.4.1.3 Data Split 196 7.4.2 Model Building 196 7.4.3 Model Fitting 197 7.4.3.1 Fit Generator 197 7.4.3.2 Validation of Accuracy and Loss Plot 197 7.4.3.3 Testing and Prediction 198 7.5 Conclusion 199 References 199 8 Personality Prediction and Handwriting Recognition Using Machine Learning 203Vishal Patil and Harsh Mathur 8.1 Introduction to the System 204 8.1.1 Assumptions and Limitations 206 8.1.1.1 Assumptions 206 8.1.1.2 Limitations 206 8.1.2 Practical Needs 206 8.1.3 Non-Functional Needs 206 8.1.4 Specifications for Hardware 207 8.1.5 Specifications for Applications 207 8.1.6 Targets 207 8.1.7 Outcomes 207 8.2 Literature Survey 208 8.2.1 Computerized Human Behavior Identification Through Handwriting Samples 208 8.2.2 Behavior Prediction Through Handwriting Analysis 209 8.2.3 Handwriting Sample Analysis for a Finding of Personality Using Machine Learning Algorithms 209 8.2.4 Personality Detection Using Handwriting Analysis 210 8.2.5 Automatic Predict Personality Based on Structure of Handwriting 210 8.2.6 Personality Identification Through Handwriting Analysis: A Review 210 8.2.7 Text Independent Writer Identification Using Convolutional Neural Network 210 8.2.8 Writer Identification Using Machine Learning Approaches 211 8.2.9 Writer Identification from HandwrittenText Lines 211 8.3 Theory 212 8.3.1 Pre-Processing 212 8.3.2 Personality Analysis 215 8.3.3 Personality Characteristics 216 8.3.4 Writer Identification 217 8.3.5 Features Used 219 8.4 Algorithm To Be Used 220 8.5 Proposed Methodology 224 8.5.1 System Flow 225 8.6 Algorithms vs. Accuracy 226 8.6.1 Implementation 228 8.7 Experimental Results 231 8.8 Conclusion 232 8.9 Conclusion and Future Scope 232 Acknowledgment 232 References 233 9 Risk Mitigation in Children With Autism Spectrum Disorder Using Brain Source Localization 237Joy Karan Singh, Deepti Kakkar and Tanu Wadhera 9.1 Introduction 238 9.2 Risk Factors Related to Autism 239 9.2.1 Assistive Technologies for Autism 240 9.2.2 Functional Connectivity as a Biomarker for Autism 241 9.2.3 Early Intervention and Diagnosis 242 9.3 Materials and Methodology 243 9.3.1 Subjects 243 9.3.2 Methods 243 9.3.3 Data Acquisition and Processing 243 9.3.4 sLORETA as a Diagnostic Tool 244 9.4 Results and Discussion 245 9.5 Conclusion and Future Scope 247 References 247 10 Predicting Chronic Kidney Disease Using Machine Learning 251Monika Gupta and Parul Gupta 10.1 Introduction 252 10.2 Machine Learning Techniques for Prediction of Kidney Failure 253 10.2.1 Analysis and Empirical Learning 254 10.2.2 Supervised Learning 255 10.2.3 Unsupervised Learning 256 10.2.3.1 Understanding and Visualization 257 10.2.3.2 Odd Detection 257 10.2.3.3 Object Completion 258 10.2.3.4 Information Acquisition 258 10.2.3.5 Data Compression 258 10.2.3.6 Capital Market 258 10.2.4 Classification 259 10.2.4.1 Training Process 260 10.2.4.2 Testing Process 260 10.2.5 Decision Tree 261 10.2.6 Regression Analysis 263 10.2.6.1 Logistic Regression 263 10.2.6.2 Ordinal Logistic Regression 265 10.2.6.3 Estimating Parameters 266 10.2.6.4 Multivariate Regression 268 10.3 Data Sources 269 10.4 Data Analysis 272 10.5 Conclusion 274 10.6 Future Scope 274 References 274 Part III: Advanced Applications of Machine Learning in Healthcare 279 11 Behavioral Modeling Using Deep Neural Network Framework for ASD Diagnosis and Prognosis 281Tanu Wadhera, Deepti Kakkar and Rajneesh Rani 11.1 Introduction 282 11.2 Automated Diagnosis of ASD 284 11.2.1 Deep Learning 289 11.2.2 Deep Learning in ASD 290 11.2.3 Transfer Learning Approach 290 11.3 Purpose of the Chapter 292 11.4 Proposed Diagnosis System 293 11.5 Conclusion 294 References 295 12 Random Forest Application of Twitter Data Sentiment Analysis in Online Social Network Prediction 299Arnav Munshi, M. Arvindhan and Thirunavukkarasu K. 12.1 Introduction 300 12.1.1 Motivation 300 12.1.2 Domain Introduction 300 12.2 Literature Survey 302 12.3 Proposed Methodology 304 12.4 Implementation 311 12.5 Conclusion 311 References 311 13 Remedy to COVID-19: Social Distancing Analyzer 315Sourabh Yadav 13.1 Introduction 315 13.2 Literature Review 318 13.3 Proposed Methodology 321 13.3.1 Person Detection 321 13.3.1.1 Frame Creation 324 13.3.1.2 Contour Detection 325 13.3.1.3 Matching with COCO Model 326 13.3.2 Distance Calculation 326 13.3.2.1 Calculation of Centroid 326 13.3.2.2 Distance Among Adjacent Centroids 327 13.4 System Implementation 328 13.5 Conclusion 333 References 334 14 IoT-Enabled Vehicle Assistance System of Highway Resourcing for Smart Healthcare and Sustainability 337Shubham Joshi and Radha Krishna Rambola 14.1 Introduction 338 14.2 Related Work 340 14.2.1 Adoption of IoT in Vehicle to Ensure Driver Safety 341 14.2.2 IoT in Healthcare System 341 14.2.3 The Technology Used in Assistance Systems 343 14.2.3.1 Adaptive Cruise Control (ACC) 343 14.2.3.2 Lane Departure Warning 343 14.2.3.3 Parking Assistance 343 14.2.3.4 Collision Avoidance System 343 14.2.3.5 Driver Drowsiness Detection 344 14.2.3.6 Automotive Night Vision 344 14.3 Objectives, Context, and Ethical Approval 344 14.4 Technical Background 345 14.4.1 IoT With Health 345 14.4.2 Machine-to-Machine (M2M) Communication 345 14.4.3 Device-to-Device (D2D) Communication 345 14.4.4 Wireless Sensor Network 346 14.4.5 Crowdsensing 346 14.5 IoT Infrastructural Components for Vehicle Assistance System 346 14.5.1 Communication Technology 346 14.5.2 Sensor Network 347 14.5.3 Infrastructural Component 348 14.5.4 Human Health Detection by Sensors 348 14.6 IoT-Enabled Vehicle Assistance System of Highway Resourcing for Smart Healthcare and Sustainability 349 14.7 Challenges in Implementation 353 14.8 Conclusion 353 References 354 15 Aids of Machine Learning for Additively Manufactured Bone Scaffold 359Nimisha Rahul Shirbhate and Sanjay Bokade 15.1 Introduction 360 15.1.1 Bone Scaffold 360 15.1.2 Bone Grafting 362 15.1.3 Comparison Bone Grafting and Bone Scaffold 363 15.2 Research Background 364 15.3 Statement of Problem 364 15.4 Research Gap 365 15.5 Significance of Research 366 15.6 Outline of Research Methodology 366 15.6.1 Customized Design of Bone Scaffold 366 15.6.2 Manufacturing Methods and Biocompatible Material 367 15.6.2.1 Conventional Scaffold Fabrication 368 15.6.2.2 Additive Manufacturing 369 15.6.2.3 Application of Additive Manufacturing/3D Printing in Healthcare 370 15.6.2.4 Automated Process Monitoring in 3D Printing Using Supervised Machine Learning 376 15.7 Conclusion 377 References 377 Index 381

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Book SynopsisAnna Tarrant's revealing research explores the dynamics and diversity of men's caring roles in low-income households at various stages of their lives. It sheds light on men's participation in care and the factors that affect it, including class, culture, work and the impact of austerity.Trade Review''This book presents a compelling account of people's engagements with biosensors. Drawing on their long experience of research in science and technology studies, the authors elucidate how people can be helped or disappointed by these new technologies.'' * Deborah Lupton, University of New South Wales *Table of Contents1. Introduction: Fathering, poverty, families and policy 2. Low-income fatherhoods in historical and political context 3. Theorising men’s participation in low-income families 4. Supporting men in low- income contexts: practitioner observations 5. Men’s caring arrangements and family trajectories 6. Familial economic circumstances and provisioning practices 7. Men’s family participation in low-income urban neighbourhoods 8. Conclusion: Men’s family participation in low-income contexts

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Book SynopsisThis book provides a current view of the research and commercial landscape of diagnostics devices, particularly those that utilize microscale technologies, intended for both patient and laboratory use. Common diagnostic devices that are based on microfluidic principles include glucose sensors for diabetic patients and over-the-counter pregnancy tests. Other diagnostic devices are being developed to quickly test a patient for bacterial and viral infections, and other diseases. The chapters, written by experts from around the world, discuss how to fabricate, apply, and market microfluidic diagnostic chips for lab and at-home use. Most importantly, the book also contains a discussion of topics relevant to the private sector, including patient-focused, market-oriented development of diagnostics devices.Chapter9 of this book is freely available as a downloadable Open Access PDF at http://www.taylorfrancis.com under a Creative Commons Attribution (CC-BY) 4.0 license.Table of ContentsPrefaceSeries EditorEditorsContributorsSection I Microfluidic Devices for Diagnostics1. Handheld Microfluidics for Point-of-CareIn Vitro Diagnostics2. Body-Worn Microfluidic Sensors3. Fabrication and Applications of Paper-Based Microfluidics4. Printed Wax-Ink Valves for Multistep Assays in PaperAnalytical Devices5. Mycofluidics: Miniaturization of Mycotoxin Analysis6. Planar Differential Mobility Spectrometry forClinical Breath DiagnosticsSection II Applications in Disease Detection7. Rapid Diagnosis of Infectious Diseases UsingMicrofluidic Systems8. Microfluidics for Tuberculosis Diagnosis: Advances,Scalability, and ChallengesSection III Practical Aspects of Developinga Commercial Diagnostic Device9. Starting with the End in Mind by Developing Diagnosticsaround User Needs10. Incorporating the Needs of Users into the Development ofDiagnostics for Global Health: A Framework and Two CaseStudiesIndex

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Book Synopsis"Compression for Clinicians: Considerations for Hearing Aid Fittings, Third Edition" explains many developments that have taken place in the world of hearing aid compression, fitting methods, and real ear measurement. Directional microphones and digital features of noise reduction, feedback reduction, and expansion are also covered. The text aims to make difficult concepts easier to understand and to explain in plain language many topics pertaining to compression. The third edition recognizes two distinct clinical populations of sensori-neural hearing loss; mild-to-moderate on the one hand, and more severe on the other. These two clinical populations are well served by a corresponding pair of compression types; wide dynamic range compression and output limiting compression. Another double distinction held throughout the text is the two-part task for all hearing aids; providing gain and also, increasing the signal-to-noise ratio. Gain is addressed by compression, while listening in noise is addressed by directional microphones and digital noise reduction.New to the Third Edition:*Includes new chapters on common clinical encounters (Chapter 1), real ear measurement (Chapter 5), and adaptive dynamic range optimization (Chapter 10)*Distinguishes between "sensory" and "neural" hearing loss and devotes a separate chapter to each of these types of sensori-neural hearing loss*Contains updated coverage of digital hearing aids, directional microphones, and digital noise reduction*Retains a strong focus on the historical development of compression from yesterday's analog hearing aids to digital hearing aids of today"Compression for Clinicians" is intended for those studying to become hearing health care professionals, including audiologists and hearing instrument practitioners. It is also intended for practicing clinicians who simply want to refresh their knowledge base concerning hearing loss and hearing aids. Clinically relevant and very thorough, it provides a relevant compass in the world of compression hearing aids.Table of ContentsPreface. Chapter 1. Common Clinical Encounters: Do We Really Know Them? Chapter 2. The Cochlea and Outer Hair Cell Damage. Chapter 3. Inner Hair Cell Damage, Traveling Wave Envelopes, and Cochlear Dead Regions. Chapter 4. Early Hearing Aid Fitting Methods: Why So Many? Chapter 5. Verification with Real Ear Measures: Yesterday and Today. Chapter 6. Compression and the DSL and NAL Fitting Methods. Chapter 7. Compression in Analog Hearing Aids: Historical Development.Chapter 8. Compression and Other Features in Digital Hearing Aids. Chapter 9. Clinical Benefits of Directional Microphones versus Digital Noise Reduction. Chapter 10. Adaptive Dynamic Range Optimization: An Alternative to WDRC. Appendix A. Classes of Hearing Aid Amplifiers. Appendix B. Answers to Review Questions of Chapter 7. Index.

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