Description

Book Synopsis

This book provides applications of machine learning in healthcare systems and seeks to close the gap between engineering and medicine by combining design and problem-solving skills of engineering with health sciences to advance healthcare treatment.

Machine Learning and Artificial Intelligence in Healthcare Systems: Tools and Techniques discusses AI-based smart paradigms for reliable prediction of infectious disease dynamics; such paradigms can help prevent disease transmission. It highlights the different aspects of using extended reality for diverse healthcare applications and aggregates the current state of research. The book offers intelligent models of the smart recommender system for personal well-being services and computer-aided drug discovery and design methods. Case studies illustrating the business processes that underlie the use of big data and health analytics to improve healthcare delivery are center stage. Innovative techniques used for extracting

Table of Contents

1. Artificial Intelligence Challenges, Principles, and Applications in Smart Healthcare Systems. 2. Systematic View and Impact of Artificial Intelligence in Smart Healthcare Systems, principles, challenges and Applications. 3. Application of Machine Learning Techniques in COVID-19 Epidemiology: A Glimpse. 4. Automated Seven-Level Skin Cancer Staging Diagnosis in Dermoscopic images using Deep Learning. 5. Ensemble Classifier Based Predictive Model for Type-2 Diabetes Mellitus Prediction. 6. Machine Learning Approaches for Analysis in Smart Healthcare Informatics. 7. Smart Approaches for Diagnosis of Brain Disorders using Artificial Intelligence. 8. Bridging the Gap Between Technology and Medicine: Approaches of Artificial Intelligence in Healthcare. 9. Brain Tumor Classification using Transfer Learning. 10. Advanced Bayesian Estimation Of Weibull In Early Stage Eye Loss Prediction In Diabetic Retinopathy. 11. Automated Sleep Staging Using Single-Channel EEG SIgnal based on Machine Learning Approaches. 12. Machine Learning Based Intelligent Assistant for Smart Healthcare. 13. AI-Enabled Sentiment Analysis on COVID-19 Vaccination: A Twitter based study. 14. An Early Diagnosis of Lung Nodule Using CT Images based on Hybrid Machine Learning techniques. 15. Early Detection of Alzheimer’s Disease Assisted by AI-Powered Human-Robot Communication.

Machine Learning and Artificial Intelligence in

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A Hardback by Tawseef Ayoub Shaikh, Saqib Hakak, Tabasum Rasool

15 in stock


    View other formats and editions of Machine Learning and Artificial Intelligence in by Tawseef Ayoub Shaikh

    Publisher: Taylor & Francis Ltd
    Publication Date: 1/22/2023 12:02:00 AM
    ISBN13: 9781032208305, 978-1032208305
    ISBN10: 1032208309

    Description

    Book Synopsis

    This book provides applications of machine learning in healthcare systems and seeks to close the gap between engineering and medicine by combining design and problem-solving skills of engineering with health sciences to advance healthcare treatment.

    Machine Learning and Artificial Intelligence in Healthcare Systems: Tools and Techniques discusses AI-based smart paradigms for reliable prediction of infectious disease dynamics; such paradigms can help prevent disease transmission. It highlights the different aspects of using extended reality for diverse healthcare applications and aggregates the current state of research. The book offers intelligent models of the smart recommender system for personal well-being services and computer-aided drug discovery and design methods. Case studies illustrating the business processes that underlie the use of big data and health analytics to improve healthcare delivery are center stage. Innovative techniques used for extracting

    Table of Contents

    1. Artificial Intelligence Challenges, Principles, and Applications in Smart Healthcare Systems. 2. Systematic View and Impact of Artificial Intelligence in Smart Healthcare Systems, principles, challenges and Applications. 3. Application of Machine Learning Techniques in COVID-19 Epidemiology: A Glimpse. 4. Automated Seven-Level Skin Cancer Staging Diagnosis in Dermoscopic images using Deep Learning. 5. Ensemble Classifier Based Predictive Model for Type-2 Diabetes Mellitus Prediction. 6. Machine Learning Approaches for Analysis in Smart Healthcare Informatics. 7. Smart Approaches for Diagnosis of Brain Disorders using Artificial Intelligence. 8. Bridging the Gap Between Technology and Medicine: Approaches of Artificial Intelligence in Healthcare. 9. Brain Tumor Classification using Transfer Learning. 10. Advanced Bayesian Estimation Of Weibull In Early Stage Eye Loss Prediction In Diabetic Retinopathy. 11. Automated Sleep Staging Using Single-Channel EEG SIgnal based on Machine Learning Approaches. 12. Machine Learning Based Intelligent Assistant for Smart Healthcare. 13. AI-Enabled Sentiment Analysis on COVID-19 Vaccination: A Twitter based study. 14. An Early Diagnosis of Lung Nodule Using CT Images based on Hybrid Machine Learning techniques. 15. Early Detection of Alzheimer’s Disease Assisted by AI-Powered Human-Robot Communication.

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