Foundations of Artificial Intelligence in Healthcare and Bioscience: A User Friendly Guide for IT Professionals, Healthcare Providers, Researchers, and Clinicians 0128244771, 9780128244777

Foundational Handbook of Artificial Intelligence in Healthcare and Bioscience: A User Friendly Guide for IT Professional

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Table of contents :
Foundations of Artificial Intelligence in Healthcare and Bioscience
Copyright
Dedication
Contents
Section I Artificial Intelligence (AI): Understanding the technology1
Section II Artificial Intelligence (AI): Applications in Health and Wellness73
List of Illustrations
Foreword by Adam Dimitrov
Foreword by Ernst Nicolitz
Preface
Postscript
Acknowledgments
Artificial intelligence (AI): Understanding the technology
Introduction
References
1 The evolution of artificial intelligence (AI)
1.1 Human intelligence
1.2 Defining artificial intelligence (AI)
References
2 The basic computer
2.1 Layers of basic computers
2.1.1 Input layer
2.1.2 Inner (hidden) layer
2.1.3 Output layer
2.2 Basic computer language and programming
2.3 Basic computer hardware
2.4 Basic computer software
2.5 Servers, internet and world wide web (www)
2.5.1 Servers
2.5.2 Internet
2.5.3 World wide web (www)
References
3 The science and technologies of artificial intelligence (AI)
3.1 The theory and science of artificial intelligence (AI)
3.2 Artificial neural network (ANN) model of artificial intelligence (AI)
3.3 AI software (algorithms)
3.3.1 Machine learning
3.3.1.1 Supervised (labeled) data
3.3.2 Neural networking and deep learning
3.3.2.1 Unsupervised (unlabeled) data
3.3.2.2 Reinforcement learning
3.4 AI hardware
3.4.1 Ram (random access memory)
3.4.2 Computer servers (file, mail, print, web, game, apps)
3.4.3 Central processing unit (CPU)
3.4.4 Graphic processing unit (GPU)
3.4.5 Accelerators [61]
3.4.6 Quantum processors using “qubits” (vs digital binary code)
3.4.7 Neuromorphic chips (“self-learning” microchips)
3.4.8 Application specific integrated circuit (ASIC)
3.4.9 Field-programmable gate array (FPGA) integrated circuit with hardware description language (HDL)
3.5 Specialized AI systems
3.5.1 Natural language processing (NLP)
3.5.2 Natural language generation (NLG)
3.5.3 Expert systems
3.5.4 “Internet of things” (IoT)
3.5.5 Cyber-physical system (CPS)
3.5.6 Big data analytics
3.5.7 Blockchain
3.5.8 Robotics
3.6 Sample AI scenarios
3.6.1 “Why is the Mona Lisa smiling?” [103]
3.6.2 The “great steak” experience [106]
References
Artificial intelligence (AI): Applications in health and wellness
Introduction
References
4 AI applications in the business and administration of health care
4.1 AI applications in government agencies (GOVs), non-governmental organizations (NGOs) and third-party health insurers
4.1.1 Primary AI applications GOVs, NGOs, and third-party health insurers (1, 2, 3)
4.1.2 Additional AI applications to GOVs, NGOs, and third-party health insurers (4, 5, 6)
4.2 Big data analytics in health care [Text #1]
4.2.1 Primary AI literature reviews of big data analytics (1, 2, 3)
4.2.2 Additional AI literature reviews of big data analytics (4, 5, 6)
4.3 Blockchain in health care [Text #2]
4.3.1 Primary AI literature reviews of blockchain (1, 2, 3)
4.3.2 Additional AI literature reviews of blockchain (4, 5, 6)
4.4 Health information and records (electronic health record or EHR) [Text #3]
4.4.1 Primary AI literature reviews of health information and records (EHR) (1, 2, 3)
4.4.2 Additional AI literature reviews of health information and records (EHR) (4, 5, 6)
4.5 Population health [Text #4]
4.5.1 Primary AI literature reviews of population health (1, 2, 3)
4.5.2 Additional AI literature reviews of population health (4, 5, 6)
4.6 Healthcare analytics (descriptive, diagnostic, predictive, prescriptive, discovery) [78] [Text #5]
4.6.1 Descriptive analytics [Text #6] [84]
4.6.2 Diagnostic analytics [Text #7] [85]
4.6.3 Predictive analytics [Text #8, page 99] [78]
4.6.4 Prescriptive analytics [Text #9, page 100] [83]
4.6.5 Primary AI literature reviews of health analytics (1, 2, 3)
4.6.6 Additional AI literature reviews of health analytics (4, 5, 6)
4.7 Precision health (aka precision medicine or personalized medicine) [Text #10]
4.7.1 Primary AI literature reviews of precision medicine/health (1, 2, 3)
4.7.2 Additional AI literature reviews of precision medicine/health (4, 5, 6)
4.8 Preventive medicine/healthcare [Text #11]
4.8.1 Primary AI literature reviews of preventive medicine/healthcare (1, 2, 3)
4.8.2 Additional AI literature reviews of preventive medicine/healthcare (4, 5, 6)
4.9 Public health [Text #12]
4.9.1 Primary AI literature reviews of public health (1, 2, 3)
4.9.2 Additional AI literature reviews of public health (4, 5, 6)
References
5 AI applications in diagnostic technologies and services
5.1 Major diagnostic technologies [4] and their AI applications
5.1.1 Diagnostic imaging
5.1.1.1 Categories of diagnostic imaging
5.1.1.1.1 AI’s influence on conventional radiography [15]
5.1.1.1.2 Literature reviews re AI’s influence on conventional radiography
5.1.1.1.3 AI’s influence on mammography
5.1.1.1.4 Literature reviews re AI’s influence on mammography
5.1.1.1.5 AI’s influence on fluoroscopy [33]
5.1.1.1.6 Literature reviews re AI’s influence on fluoroscopy
5.1.1.1.7 AI’s influence on radiomics
5.1.1.1.8 Literature reviews re AIs influence on radiomics
5.1.1.1.9 AI’s influence on computed tomography (CT or CAT) scans [53]
5.1.1.1.10 Literature reviews re AI’s influence on computed tomography (CT or CAT) scans
5.1.1.1.11 AI’s influence on MRI scans
5.1.1.1.12 Literature reviews re AI’s influence on MRI scans
5.1.1.1.13 AI’s influence on nuclear medicine scans [74]
5.1.1.1.14 Literature reviews re AI’s influence on nuclear medicine scans
5.1.1.1.15 AI’s influence on ultrasound (sonography) [78]
5.1.1.1.16 Literature reviews re AI’s influence on ultrasound (sonography)
5.1.1.1.17 AI’s influence on endoscopy [90]
5.1.1.1.18 Literature reviews re: AI’s influence on endoscopy
5.1.1.1.19 AI’s influence on fundus imaging [97]
5.1.1.1.20 Literature reviews re AI’s influence on fundus imaging
5.1.1.1.21 AI’s influence on medical (clinical) photography
5.1.1.1.22 Literature reviews re AI’s influence on medical (clinical) photography
5.1.2 Laboratory (clinical diagnostic) testing
5.1.2.1 AI’s influence on laboratory testing
5.1.3 Genetic and genomic screening and diagnosis
5.1.3.1 The science
5.1.3.2 Cytogenetics
5.1.3.3 Genetic testing [128]
5.1.3.4 Big data analytics in genomics [130]
5.1.3.5 AI in genetic cancer screening
5.1.3.6 AI in immunogenetics (see also Immunology, Chapters 6 and 7)
5.1.3.7 Genetics, precision medicine and AI
5.1.3.8 Literature reviews re AI’s influence on genetics and genomics
5.2 Additional diagnostic technologies and their AI applications
5.2.1 Vital signs
5.2.2 Electrodiagnosis
5.2.3 Telemedicine (aka telehealth)
5.2.4 Chatbots
5.2.5 Expert systems
5.2.5.1 Literature reviews re AI’s influences on “additional diagnostic technologies”
References
6 Current AI applications in medical therapies and services
6.1 Medical care (primary, secondary, tertiary, quaternary care)
6.1.1 Big data analytics and AI in medical care
6.1.2 Health information and records (EHR) and AI in medical care
6.1.3 Research/clinical trials and AI in medical care
6.1.4 Blockchain and AI in medical care
6.1.5 Internet of Things (IoT) and AI in medical care [15]
6.1.6 Telehealth and AI in medical care [16]
6.1.7 Chatbots and AI in medical care [16]
6.1.8 Natural language processing (NLP) and AI in medical care
6.1.9 Expert systems and AI in medical care
6.1.10 Robotics and AI in medical care
6.1.11 Population health (demographics and epidemiology) and AI in medical care
6.1.12 Precision medicine/health (personalized health) and AI in medical care
6.1.13 Healthcare analytics and AI in medical care
6.1.14 Preventive health and AI in medical care
6.1.15 Public health and AI in medical care
6.1.16 Access and availability and AI in medical care
6.2 Pharmaceutical and biopharmaceutical care
6.2.1 Big data analytics and AI in pharmaceutical care
6.2.2 Health information and records (EHR) and AI in pharmaceutical care
6.2.3 Research/clinical trials and AI in pharmaceutical care
6.2.4 Blockchain and AI in pharmaceutical care
6.2.5 Internet of Things (IoT) and AI in pharmaceutical care
6.2.6 Telehealth and AI in pharmaceutical care
6.2.7 Chatbots and AI in pharmaceutical care
6.2.8 Natural language processing (NLP) and AI in pharmaceutical care
6.2.9 Expert systems and AI in pharmaceutical care
6.2.10 Robotics and AI in pharmaceutical care
6.2.11 Population health (demographics and epidemiology) and AI in pharmaceutical care
6.2.12 Precision medicine/health (personalized health) and AI in pharmaceutical care
6.2.13 Healthcare analytics and AI in pharmaceutical care
6.2.14 Preventive health and AI in pharmaceutical care
6.2.15 Public health and AI in pharmaceutical care
6.2.16 Access and availability and AI in pharmaceutical care
6.3 Hospital care
6.3.1 Big data analytics and AI in hospital care
6.3.2 Health information and records (EHR) and AI in hospital care
6.3.3 Research/clinical trials and AI in hospital care
6.3.4 Blockchain and AI in hospital care
6.3.5 Internet of Things (IoT) and AI in hospital care [15]
6.3.6 Telehealth and AI in hospital care [114]
6.3.7 Chatbots and AI in hospital care
6.3.8 Natural language processing (NLP) and AI in hospital care
6.3.9 Expert systems and AI in hospital care
6.3.10 Robotics and AI in hospital care
6.3.11 Population health (demographics and epidemiology) and AI in hospital care
6.3.12 Precision medicine/health (personalized health) and AI in hospital care
6.3.13 Healthcare analytics and AI in hospital care
6.3.14 Public health and AI in hospital care [136]
6.3.15 Access and availability and AI in hospital care
6.4 Nursing care
6.4.1 Big data analytics and AI in nursing care
6.4.2 Health information and records (EHR) and AI in nursing care
6.4.3 Research/clinical trials and AI in nursing care
6.4.4 Blockchain and AI in nursing care
6.4.5 Internet of Things (IoT) and AI in nursing care
6.4.6 Telehealth and AI in nursing care
6.4.7 Chatbots and AI in nursing care
6.4.8 Natural language processing (NLP), and AI in nursing care
6.4.9 Expert systems and AI in nursing care
6.4.10 Robotics and AI in nursing care
6.4.11 Population health (demographics and epidemiology) and AI in nursing care
6.4.12 Precision medicine/health (personalized health) and AI in nursing care
6.4.13 Healthcare analytics and AI in nursing care
6.4.14 Preventive health and AI in nursing care
6.4.15 Public health and AI in nursing care
6.4.16 Access and availability and AI in nursing care
6.5 Home health care, nursing homes and hospice care
6.5.1 Big data analytics and AI in home health, nursing homes, and hospice care
6.5.2 Health information and records (EHR) and AI in home health, nursing homes, and hospice care
6.5.3 Research/clinical trials and AI in home health, nursing homes, and hospice care
6.5.4 Blockchain and AI in home health, nursing homes, and hospice care
6.5.5 Internet of Things (IoT) and AI in home health, nursing homes, and hospice care
6.5.6 Telehealth and AI in home health, nursing homes, and hospice care
6.5.7 Chatbots and AI in home health, nursing homes, and hospice care
6.5.8 Natural language processing (NLP) and AI in home health, nursing homes, and hospice care
6.5.9 Robotics and AI in home health, nursing homes, and hospice care
6.5.10 Population health (demographics and epidemiology) and AI in home health, nursing homes, and hospice care
6.5.11 Precision medicine/health (personalized health) and AI in home health, nursing homes, and hospice care
6.5.12 Healthcare analytics and AI in home health, nursing homes, and hospice care
6.5.13 Preventive health and AI in home health, nursing homes, and hospice care
6.5.14 Public health and AI in home health, nursing homes, and hospice care
6.5.15 Access and availability and AI in home health, nursing homes, and hospice care
6.6 Concurrent medical conditions (“comorbidity,” aka “multimorbidity”)
6.6.1 Big data analytics and AI in concurrent medical conditions (“comorbidity”)
6.6.2 Health information and records (EHR) and AI in concurrent medical conditions (“comorbidity”)
6.6.3 Research/clinical trials and AI in concurrent medical conditions (“comorbidity”)
6.6.4 Blockchain and AI in concurrent medical conditions (“comorbidity”)
6.6.5 Telehealth and AI in concurrent medical conditions (“comorbidity”)
6.6.6 Chatbots and AI in concurrent medical conditions (“comorbidity”)
6.6.7 Natural language processing (NLP) and AI in concurrent medical conditions (“comorbidity”)
6.6.8 Expert systems and AI in concurrent medical conditions (“comorbidity”)
6.6.9 Robotics and AI in concurrent medical conditions (“comorbidity”)
6.6.10 Population health (demographics and epidemiology) and AI in concurrent medical conditions (“comorbidity”)
6.6.11 Precision medicine/health (personalized health) and AI in concurrent medical conditions (“comorbidity”)
6.6.12 Healthcare analytics and AI in concurrent medical conditions (“comorbidity”)
6.6.13 Preventive health and AI in concurrent medical conditions (“comorbidity”)
6.6.14 Public health and AI in concurrent medical conditions (“comorbidity”)
6.6.15 Access and availability and AI in concurrent medical conditions (“comorbidity”)
6.7 Medical/surgical robotics
6.7.1 Big data analytics and AI in medical/surgical robotics
6.7.2 Health information and records (EHR) and AI in medical/surgical robotics
6.7.3 Research/clinical trials and AI in medical/surgical robotics
6.7.4 Blockchain and AI in medical/surgical robotics
6.7.5 Internet of Things (IoT) and AI in medical/surgical robotics
6.7.6 Telehealth and AI in medical/surgical robotics
6.7.7 Chatbots and AI in medical/surgical robotics
6.7.8 Natural language processing (NLP) and AI in medical/surgical robotics
6.7.9 Expert systems and AI in medical/surgical robotics
6.7.10 Precision medicine/health (personalized health) and AI in medical/surgical robotics
6.7.11 Healthcare analytics and AI in medical/surgical robotics
6.7.12 Preventive health and AI in medical/surgical robotics
6.7.13 Public health and AI in medical/surgical robotics
6.7.14 Access and availability and AI in medical/surgical robotics
6.8 Stem cells and regenerative medicine
6.8.1 The basic bioscience of stem cells and regenerative medicine [276]
6.8.2 Big data analytics and AI in stem cells and regenerative medicine
6.8.3 Research/clinical trials and AI in stem cells and regenerative medicine
6.8.4 Blockchain and AI in stem cells and regenerative medicine
6.8.5 Internet of Things (IoT) and AI in stem cells and regenerative medicine
6.8.6 3-D bioprinting and AI in stem cells and regenerative medicine
6.8.7 Chatbots and AI in stem cells and regenerative medicine
6.8.8 Natural language processing (NLP) and AI in stem cells and regenerative medicine
6.8.9 Expert systems and AI in stem cells and regenerative medicine
6.8.10 Robotics and AI in stem cells and regenerative medicine
6.8.11 Precision medicine/health (personalized health) and AI in stem cells and regenerative medicine
6.8.12 Healthcare analytics and AI in stem cells and regenerative medicine
6.8.13 Preventive health and AI in stem cells and regenerative medicine
6.8.14 Public health and AI in stem cells and regenerative medicine
6.8.15 Access and availability and AI in stem cells and regenerative medicine
6.9 Genetics and genomics therapies
6.9.1 Big data analytics and AI in genetics and genomics
6.9.2 Health information and records (EHR) and AI in genetics and genomics therapies
6.9.3 Research/clinical trials and AI in genetics and genomics
6.9.4 Blockchain and AI in genetics and genomics
6.9.5 Internet of Things (IoT) and AI in genetics and genomics
6.9.6 Telehealth and AI in genetics and genomics
6.9.7 Chatbots and AI in genetics and genomics
6.9.8 Natural language processing (NLP) and AI in genetics and genomics
6.9.9 Expert systems and AI in genetics and genomics
6.9.10 Robotics and AI in genetics and genomics
6.9.11 Population health (demographics and epidemiology) and AI in genetics and genomics
6.9.12 Precision medicine/health (personalized health) and AI in genetics and genomics
6.9.13 Healthcare analytics (and bioinformatics) and AI in genetics and genomics
6.9.14 Preventive health and AI in genetics and genomics
6.9.15 Public health and AI in genetics and genomics
6.9.16 Access and availability and AI in genetics and genomics
References
7 AI applications in prevalent diseases and disorders
7.1 Immunology and autoimmune disease
7.1.1 Pathogenesis and etiologies of immunology and autoimmune disease
7.1.2 Clinical presentations in immunology and autoimmune disease
7.1.3 Current treatment approaches and AI applications in immunology and autoimmune disease
7.1.3.1 Stem cell transplantation
7.1.3.2 CRISPR-Cas9 (gene editing)
7.1.3.3 CAR-T cell (gene replacement)
7.1.4 Research and future AI considerations in immunology and autoimmune disease
7.2 Genetic and genomic disorders
7.2.1 Description and etiology of genetic and genomic disorders
7.2.2 Clinical presentations in genetic and genomic disorders
7.2.3 Current treatment approaches and AI applications in genetic and genomic disorders
7.2.4 Research and future AI considerations in genetic and genomic disorders
7.3 Cancers
7.3.1 Description and etiology of cancers
7.3.2 Clinical presentations in cancers
7.3.3 Current treatment approaches and AI applications in cancers
7.3.4 Research and future AI considerations in cancers
7.4 Vascular (cardiovascular and cerebrovascular) disorders
7.4.1 Description and etiology of cardio and cerebrovascular disorders
7.4.1.1 Structures of the cardiovascular systems
7.4.1.2 Structures of the cerebrovascular system
7.4.1.3 Diseases and disorders of the cardiovascular system
7.4.1.4 Diseases and disorders of the cerebrovascular system
7.4.2 Current treatment approaches and AI applications in vascular disorders
7.4.3 Research and future AI considerations in vascular care
7.4.3.1 Diagnostic and screening considerations in vascular care
7.4.3.2 Emerging AI applications in vascular treatment and prevention
7.5 Diabetes (type 1 and 2)
7.5.1 Description and etiology of diabetes (type 1 and 2)
7.5.1.1 Type 1 diabetes
7.5.1.2 Type 2 diabetes (mellitus)
7.5.2 Clinical presentations in diabetes (type 1 and 2)
7.5.2.1 Type 1 diabetes
7.5.2.2 Type 2 diabetes mellitus
7.5.3 Current treatment approaches to diabetes (type 1 and 2)
7.5.3.1 Type 1 diabetes [163]
7.5.3.2 Type 2 diabetes [164]
7.5.4 Research and future AI applications in diabetes (type 1 and 2)
7.5.4.1 Type 1 diabetes
7.5.4.2 Type 2 diabetes
7.6 Neurological and sensory disorders and diseases
7.6.1 Neuroanatomy, etiologies, clinical considerations associated with neurological and sensory disorders
7.6.1.1 The central nervous system (CNS) neuroanatomy [177]
7.6.1.2 Central nervous system (CNS) clinical considerations (by etiology) [178]
7.6.1.3 Peripheral nervous system (PNS) neuroanatomy [179]
7.6.1.4 Peripheral nervous system (PNS) clinical considerations (by etiology) [180]
7.6.1.5 Sensory systems [181]
7.6.2 Research and AI considerations in neurological and sensory disorders
7.7 Musculoskeletal disorders (MSDs)
7.7.1 Musculoskeletal disorders (MSD) and diseases and associated AI applications
7.8 Integumentary system and exocrine glands
7.8.1 Dermatology
7.8.2 Integumentary system disorders and diseases and associated AI applications
7.9 Endocrine glands
7.9.1 Endocrine disorders and diseases and associated AI applications
7.10 Digestive and excretory systems
7.10.1 Digestive and excretory disorders and diseases and associated AI applications
7.11 Renal system and urinary system
7.11.1 Renal and urinary disorders and diseases and associated AI applications
7.12 Respiratory (pulmonary) system
7.12.1 Respiratory system diseases and disorders and associated AI applications
7.13 Reproductive systems
7.13.1 Female reproductive system [366]
7.13.2 Female reproductive cycle
7.13.2.1 Disease conditions of the female reproductive system with recent, related AI programs
7.13.3 Male reproductive system [366]
7.13.3.1 Male reproductive process
7.13.3.2 Functional disorders of the male reproduction system with recent, related AI programs
7.13.4 Disease conditions of the male reproduction system with recent AI programs
7.14 Physical injuries, wounds and disabilities
7.14.1 Fatal injury data
7.14.2 Nonfatal injury data
7.14.3 Disabilities
7.15 Infectious disease
7.16 Human development, aging, degeneration and death
7.17 Chronic disease
7.18 Mental and behavioral disorders
7.19 Nutrition and exercise (preventive care)
7.19.1 Physical exercise
7.19.2 Nutrition
References
8 SARS-CoV-2 and the COVID-19 pandemic
8.1 Background
8.1.1 Definitions
8.1.2 History of pandemics
8.1.2.1 Historical overview
8.1.2.2 Recent history
8.1.3 Incidence and prevalence of COVID-19
8.2 Pathogenesis and bioscience considerations for SARS-CoV-2
8.2.1 Mechanisms
8.2.2 Theories
8.2.3 Life cycle of SARS-CoV-2
8.2.4 Review of AI regarding the pathogenesis of SARS-CoV-2
8.3 Clinical considerations regarding SARS-CoV-2 infection
8.3.1 Clinical manifestations (signs and symptoms)
8.3.2 Diagnostic testing
8.3.2.1 Antigen testing
8.3.2.2 Molecular genetic test (PCR test)
8.3.2.3 Antibody testing
8.4 Treatment and management strategies
8.4.1 General measures
8.4.1.1 Basic preventive steps
8.4.1.2 Mitigation
8.4.1.3 Contact tracing
8.4.1.4 Modeling
8.4.1.5 Herd immunity and R Naught (RO or RO)
8.4.2 Therapeutics
8.4.2.1 Monoclonal antibodies
8.4.2.2 Convalescent plasma (serum)
8.4.2.3 Hydroxychloroquine (Plaquenil®) combined with azithromycin (Zithromax®)
8.4.2.4 Remdesivir
8.4.2.5 Dexamethasone (and corticosteroids)
8.4.2.6 RNA screening
8.4.3 Vaccine (immunization)
8.4.4 CRISPR-Cas13 and RNA screening
8.4.5 Immunoinformatics
8.4.6 Review of AI for clinical considerations for coronavirus infections
8.5 Epidemiology and public health considerations in COVID-19
8.5.1 Current epidemiologic considerations
8.5.2 Review of AI for epidemiology and public health considerations
Conclusion
References
Epilogue
References
Glossary of terminology
Glossary of abbreviations
Index
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Foundations of Artificial Intelligence in Healthcare and Bioscience

Foundations of Artificial Intelligence in Healthcare and Bioscience A User Friendly Guide for IT Professionals, Healthcare Providers, Researchers, and Clinicians

Louis J. Catania Nicolitz Eye Consultants, Jacksonville, FL, United States

Academic Press is an imprint of Elsevier 125 London Wall, London EC2Y 5AS, United Kingdom 525 B Street, Suite 1650, San Diego, CA 92101, United States 50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, United Kingdom Copyright © 2021 Elsevier Inc. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions. This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein). Notices Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility. To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein. British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the Library of Congress ISBN: 978-0-12-824477-7 For Information on all Academic Press publications visit our website at https://www.elsevier.com/books-and-journals

Publisher: Mara Conner Acquisitions Editor: Chris Katsaropoulos Editorial Project Manager: Rafael G. Trombaco Production Project Manager: Niranjan Bhaskaran Cover Designer: Christian J. Bilbow Typeset by MPS Limited, Chennai, India

Dedication To my wife Stephanie, Thank you for your love and support To all the health care workers who have served us all during the COVID-19 pandemic and every day, Thank you To the families of all those lost to the COVID-19 pandemic, My deepest sympathies

Contents List of Illustrations

xxv

Foreword by Adam Dimitrov Foreword by Ernst Nicolitz Preface

xxxi

xxxiii

Acknowledgments

Section I

xxix

xxxv

Artificial Intelligence (AI): Understanding the technology

Introduction References 1.

2.

1 1 6

The evolution of artificial intelligence (AI)

7

1.1 Human intelligence

7

1.2 Defining artificial intelligence (AI)

8

References

11

The basic computer

13

2.1 Layers of basic computers

14

2.1.1 Input layer

14

2.1.2 Inner (hidden) layer

16

2.1.3 Output layer

18

2.2 Basic computer language and programming

19

2.3 Basic computer hardware

21

2.4 Basic computer software

22 vii

viii

Contents

2.5 Servers, internet and world wide web (www)

3.

23

2.5.1 Servers

23

2.5.2 Internet

25

2.5.3 World wide web (www)

26

References

26

The science and technologies of artificial intelligence (AI)

29

3.1 The theory and science of artificial intelligence (AI)

29

3.2 Artificial neural network (ANN) model of artificial intelligence (AI)

31

3.3 AI software (algorithms)

36

3.3.1 Machine learning

38

3.3.1.1 Supervised (labeled) data

38

3.3.2 Neural networking and deep learning

40

3.3.2.1 Unsupervised (unlabeled) data

40

3.3.2.2 Reinforcement learning

42

3.4 AI hardware

46

3.4.1 Ram (random access memory)

46

3.4.2 Computer servers (file, mail, print, web, game, apps)

47

3.4.3 Central processing unit (CPU)

47

3.4.4 Graphic processing unit (GPU)

48

3.4.5 Accelerators

48

3.4.6 Quantum processors using “qubits” (vs digital binary code)

49

3.4.7 Neuromorphic chips (“self-learning” microchips)

49

3.4.8 Application specific integrated circuit (ASIC)

50

3.4.9 Field-programmable gate array (FPGA) integrated circuit with hardware description language (HDL)

50

3.5 Specialized AI systems

51

3.5.1 Natural language processing (NLP)

51

3.5.2 Natural language generation (NLG)

52

Contents

3.5.3 Expert systems

53

3.5.4 “Internet of things” (IoT)

55

3.5.5 Cyber-physical system (CPS)

55

3.5.6 Big data analytics

56

3.5.7 Blockchain

59

3.5.8 Robotics

60

3.6 Sample AI scenarios

64

3.6.2 The “great steak” experience

67

Artificial Intelligence (AI): Applications in Health and Wellness

Introduction References 4.

64

3.6.1 “Why is the Mona Lisa smiling?” References

Section II

ix

68

73 73 77

AI applications in the business and administration of health care

79

4.1 AI applications in government agencies (GOVs), non-governmental organizations (NGOs) and third-party health insurers

79

4.1.1 Primary AI applications GOVs, NGOs, and third-party health insurers (1, 2, 3)

79

4.1.2 Additional AI applications to GOVs, NGOs, and third-party health insurers (4, 5, 6)

82

4.2 Big data analytics in health care [Text #1]

83

4.2.1 Primary AI literature reviews of big data analytics (1, 2, 3)

83

4.2.2 Additional AI literature reviews of big data analytics (4, 5, 6)

85

x

Contents

4.3 Blockchain in health care [Text #2]

85

4.3.1 Primary AI literature reviews of blockchain (1, 2, 3)

86

4.3.2 Additional AI literature reviews of blockchain (4, 5, 6)

88

4.4 Health information and records (electronic health record or EHR) [Text #3]

88

4.4.1 Primary AI literature reviews of health information and records (EHR) (1, 2, 3)

89

4.4.2 Additional AI literature reviews of health information and records (EHR) (4, 5, 6)

91

4.5 Population health [Text #4]

91

4.5.1 Primary AI literature reviews of population health (1, 2, 3)

95

4.5.2 Additional AI literature reviews of population health (4, 5, 6)

97

4.6 Healthcare analytics (descriptive, diagnostic, predictive, prescriptive, discovery) [Text #5]

97

4.6.1 Descriptive analytics [Text #6]

98

4.6.2 Diagnostic analytics [Text #7]

99

4.6.3 Predictive analytics [Text #8]

99

4.6.4 Prescriptive analytics [Text #9]

100

4.6.5 Primary AI literature reviews of health analytics (1, 2, 3)

100

4.6.6 Additional AI literature reviews of health analytics (4, 5, 6)

101

4.7 Precision health (aka precision medicine or personalized medicine) [Text #10]

101

4.7.1 Primary AI literature reviews of precision medicine/health (1, 2, 3)

102

4.7.2 Additional AI literature reviews of precision medicine/health (4, 5, 6)

106

4.8 Preventive medicine/healthcare [Text #11] 4.8.1 Primary AI literature reviews of preventive medicine/healthcare (1, 2, 3)

106 108

Contents

4.8.2 Additional AI literature reviews of preventive medicine/healthcare (4, 5, 6) 4.9 Public health [Text #12]

5.

xi

110 111

4.9.1 Primary AI literature reviews of public health (1, 2, 3)

112

4.9.2 Additional AI literature reviews of public health (4, 5, 6)

116

References

117

AI applications in diagnostic technologies and services

125

5.1 Major diagnostic technologies and their AI applications

127

5.1.1 Diagnostic imaging 5.1.1.1 Categories of diagnostic imaging 5.1.2 Laboratory (clinical diagnostic) testing 5.1.2.1 AI’s influence on laboratory testing 5.1.3 Genetic and genomic screening and diagnosis

129 131 158 159 168

5.1.3.1 The science

169

5.1.3.2 Cytogenetics

173

5.1.3.3 Genetic testing

173

5.1.3.4 Big data analytics in genomics

175

5.1.3.5 AI in genetic cancer screening

176

5.1.3.6 AI in immunogenetics

176

5.1.3.7 Genetics, precision medicine and AI

177

5.1.3.8 Literature reviews re AI’s influence on genetics and genomics

177

5.2 Additional diagnostic technologies and their AI applications

178

5.2.1 Vital signs

179

5.2.2 Electrodiagnosis

180

5.2.3 Telemedicine (aka telehealth)

182

xii

Contents

5.2.4 Chatbots

185

5.2.5 Expert systems

187

5.2.5.1 Literature reviews re AI’s influences on “additional diagnostic technologies”

6.

189

References

190

Current AI applications in medical therapies and services

199

6.1 Medical care (primary, secondary, tertiary, quaternary care)

200

6.1.1 Big data analytics and AI in medical care

201

6.1.2 Health information and records (EHR) and AI in medical care

202

6.1.3 Research/clinical trials and AI in medical care

202

6.1.4 Blockchain and AI in medical care

203

6.1.5 Internet of Things (IoT) and AI in medical care

203

6.1.6 Telehealth and AI in medical care

204

6.1.7 Chatbots and AI in medical care

204

6.1.8 Natural language processing (NLP) and AI in medical care

205

6.1.9 Expert systems and AI in medical care

205

6.1.10 Robotics and AI in medical care

206

6.1.11 Population health (demographics and epidemiology) and AI in medical care

207

6.1.12 Precision medicine/health (personalized health) and AI in medical care

207

6.1.13 Healthcare analytics and AI in medical care

208

6.1.14 Preventive health and AI in medical care

209

6.1.15 Public health and AI in medical care

209

6.1.16 Access and availability and AI in medical care

211

6.2 Pharmaceutical and biopharmaceutical care

212

6.2.1 Big data analytics and AI in pharmaceutical care

212

6.2.2 Health information and records (EHR) and AI in pharmaceutical care

212

Contents xiii

6.2.3 Research/clinical trials and AI in pharmaceutical care

213

6.2.4 Blockchain and AI in pharmaceutical care

214

6.2.5 Internet of Things (IoT) and AI in pharmaceutical care

215

6.2.6 Telehealth and AI in pharmaceutical care

215

6.2.7 Chatbots and AI in pharmaceutical care

216

6.2.8 Natural language processing (NLP) and AI in pharmaceutical care

216

6.2.9 Expert systems and AI in pharmaceutical care

217

6.2.10 Robotics and AI in pharmaceutical care

217

6.2.11 Population health (demographics and epidemiology) and AI in pharmaceutical care

217

6.2.12 Precision medicine/health (personalized health) and AI in pharmaceutical care

218

6.2.13 Healthcare analytics and AI in pharmaceutical care

218

6.2.14 Preventive health and AI in pharmaceutical care

219

6.2.15 Public health and AI in pharmaceutical care

219

6.2.16 Access and availability and AI in pharmaceutical care

220

6.3 Hospital care

220

6.3.1 Big data analytics and AI in hospital care

220

6.3.2 Health information and records (EHR) and AI in hospital care

220

6.3.3 Research/clinical trials and AI in hospital care

221

6.3.4 Blockchain and AI in hospital care

221

6.3.5 Internet of Things (IoT) and AI in hospital care

222

6.3.6 Telehealth and AI in hospital care

222

6.3.7 Chatbots and AI in hospital care

223

6.3.8 Natural language processing (NLP) and AI in hospital care

223

6.3.9 Expert systems and AI in hospital care

224

6.3.10 Robotics and AI in hospital care

224

xiv

Contents

6.3.11 Population health (demographics and epidemiology) and AI in hospital care

225

6.3.12 Precision medicine/health (personalized health) and AI in hospital care

225

6.3.13 Healthcare analytics and AI in hospital care

226

6.3.14 Public health and AI in hospital care

226

6.3.15 Access and availability and AI in hospital care

227

6.4 Nursing care

227

6.4.1 Big data analytics and AI in nursing care

227

6.4.2 Health information and records (EHR) and AI in nursing care

228

6.4.3 Research/clinical trials and AI in nursing care

228

6.4.4 Blockchain and AI in nursing care

228

6.4.5 Internet of Things (IoT) and AI in nursing care

229

6.4.6 Telehealth and AI in nursing care

229

6.4.7 Chatbots and AI in nursing care

230

6.4.8 Natural language processing (NLP), and AI in nursing care

230

6.4.9 Expert systems and AI in nursing care

231

6.4.10 Robotics and AI in nursing care

231

6.4.11 Population health (demographics and epidemiology) and AI in nursing care

232

6.4.12 Precision medicine/health (personalized health) and AI in nursing care

232

6.4.13 Healthcare analytics and AI in nursing care

233

6.4.14 Preventive health and AI in nursing care

233

6.4.15 Public health and AI in nursing care

234

6.4.16 Access and availability and AI in nursing care

234

6.5 Home health care, nursing homes and hospice care 6.5.1 Big data analytics and AI in home health, nursing homes, and hospice care

235 235

Contents

xv

6.5.2 Health information and records (EHR) and AI in home health, nursing homes, and hospice care

235

6.5.3 Research/clinical trials and AI in home health, nursing homes, and hospice care

236

6.5.4 Blockchain and AI in home health, nursing homes, and hospice care

236

6.5.5 Internet of Things (IoT) and AI in home health, nursing homes, and hospice care

237

6.5.6 Telehealth and AI in home health, nursing homes, and hospice care

237

6.5.7 Chatbots and AI in home health, nursing homes, and hospice care

238

6.5.8 Natural language processing (NLP) and AI in home health, nursing homes, and hospice care

238

6.5.9 Robotics and AI in home health, nursing homes, and hospice care

239

6.5.10 Population health (demographics and epidemiology) and AI in home health, nursing homes, and hospice care

239

6.5.11 Precision medicine/health (personalized health) and AI in home health, nursing homes, and hospice care

239

6.5.12 Healthcare analytics and AI in home health, nursing homes, and hospice care

240

6.5.13 Preventive health and AI in home health, nursing homes, and hospice care

240

6.5.14 Public health and AI in home health, nursing homes, and hospice care

241

6.5.15 Access and availability and AI in home health, nursing homes, and hospice care

241

6.6 Concurrent medical conditions (“comorbidity,” aka “multimorbidity”)

242

6.6.1 Big data analytics and AI in concurrent medical conditions (“comorbidity”)

243

6.6.2 Health information and records (EHR) and AI in concurrent medical conditions (“comorbidity”)

243

xvi

Contents

6.6.3 Research/clinical trials and AI in concurrent medical conditions (“comorbidity”)

244

6.6.4 Blockchain and AI in concurrent medical conditions (“comorbidity”)

244

6.6.5 Telehealth and AI in concurrent medical conditions (“comorbidity”)

245

6.6.6 Chatbots and AI in concurrent medical conditions (“comorbidity”)

246

6.6.7 Natural language processing (NLP) and AI in concurrent medical conditions (“comorbidity”)

246

6.6.8 Expert systems and AI in concurrent medical conditions (“comorbidity”)

247

6.6.9 Robotics and AI in concurrent medical conditions (“comorbidity”)

247

6.6.10 Population health (demographics and epidemiology) and AI in concurrent medical conditions (“comorbidity”)

248

6.6.11 Precision medicine/health (personalized health) and AI in concurrent medical conditions (“comorbidity”)

248

6.6.12 Healthcare analytics and AI in concurrent medical conditions (“comorbidity”)

249

6.6.13 Preventive health and AI in concurrent medical conditions (“comorbidity”)

249

6.6.14 Public health and AI in concurrent medical conditions (“comorbidity”)

250

6.6.15 Access and availability and AI in concurrent medical conditions (“comorbidity”)

250

6.7 Medical/surgical robotics

251

6.7.1 Big data analytics and AI in medical/surgical robotics

251

6.7.2 Health information and records (EHR) and AI in medical/surgical robotics

251

6.7.3 Research/clinical trials and AI in medical/surgical robotics

252

6.7.4 Blockchain and AI in medical/surgical robotics

252

Contents

xvii

6.7.5 Internet of Things (IoT) and AI in medical/surgical robotics

253

6.7.6 Telehealth and AI in medical/surgical robotics

253

6.7.7 Chatbots and AI in medical/surgical robotics

254

6.7.8 Natural language processing (NLP) and AI in medical/surgical robotics

255

6.7.9 Expert systems and AI in medical/surgical robotics

255

6.7.10 Precision medicine/health (personalized health) and AI in medical/surgical robotics

256

6.7.11 Healthcare analytics and AI in medical/surgical robotics

256

6.7.12 Preventive health and AI in medical/surgical robotics

256

6.7.13 Public health and AI in medical/surgical robotics

257

6.7.14 Access and availability and AI in medical/surgical robotics

257

6.8 Stem cells and regenerative medicine

257

6.8.1 The basic bioscience of stem cells and regenerative medicine

258

6.8.2 Big data analytics and AI in stem cells and regenerative medicine

259

6.8.3 Research/clinical trials and AI in stem cells and regenerative medicine

260

6.8.4 Blockchain and AI in stem cells and regenerative medicine

260

6.8.5 Internet of Things (IoT) and AI in stem cells and regenerative medicine

261

6.8.6 3-D bioprinting and AI in stem cells and regenerative medicine

261

6.8.7 Chatbots and AI in stem cells and regenerative medicine

261

6.8.8 Natural language processing (NLP) and AI in stem cells and regenerative medicine

262

xviii

Contents

6.8.9 Expert systems and AI in stem cells and regenerative medicine

262

6.8.10 Robotics and AI in stem cells and regenerative medicine

263

6.8.11 Precision medicine/health (personalized health) and AI in stem cells and regenerative medicine

263

6.8.12 Healthcare analytics and AI in stem cells and regenerative medicine

264

6.8.13 Preventive health and AI in stem cells and regenerative medicine

264

6.8.14 Public health and AI in stem cells and regenerative medicine

265

6.8.15 Access and availability and AI in stem cells and regenerative medicine

265

6.9 Genetics and genomics therapies

265

6.9.1 Big data analytics and AI in genetics and genomics

266

6.9.2 Health information and records (EHR) and AI in genetics and genomics therapies

268

6.9.3 Research/clinical trials and AI in genetics and genomics

268

6.9.4 Blockchain and AI in genetics and genomics

269

6.9.5 Internet of Things (IoT) and AI in genetics and genomics

269

6.9.6 Telehealth and AI in genetics and genomics

270

6.9.7 Chatbots and AI in genetics and genomics

270

6.9.8 Natural language processing (NLP) and AI in genetics and genomics

271

6.9.9 Expert systems and AI in genetics and genomics

271

6.9.10 Robotics and AI in genetics and genomics

272

6.9.11 Population health (demographics and epidemiology) and AI in genetics and genomics

272

6.9.12 Precision medicine/health (personalized health) and AI in genetics and genomics

273

Contents

7.

xix

6.9.13 Healthcare analytics (and bioinformatics) and AI in genetics and genomics

273

6.9.14 Preventive health and AI in genetics and genomics

274

6.9.15 Public health and AI in genetics and genomics

275

6.9.16 Access and availability and AI in genetics and genomics

275

References

276

AI applications in prevalent diseases and disorders

293

7.1 Immunology and autoimmune disease

294

7.1.1 Pathogenesis and etiologies of immunology and autoimmune disease

295

7.1.2 Clinical presentations in immunology and autoimmune disease

298

7.1.3 Current treatment approaches and AI applications in immunology and autoimmune disease

300

7.1.3.1 Stem cell transplantation

302

7.1.3.2 CRISPR-Cas9 (gene editing)

303

7.1.3.3 CAR-T cell (gene replacement)

305

7.1.4 Research and future AI considerations in immunology and autoimmune disease 7.2 Genetic and genomic disorders

306 308

7.2.1 Description and etiology of genetic and genomic disorders

309

7.2.2 Clinical presentations in genetic and genomic disorders

310

7.2.3 Current treatment approaches and AI applications in genetic and genomic disorders

312

7.2.4 Research and future AI considerations in genetic and genomic disorders 7.3 Cancers

313 314

7.3.1 Description and etiology of cancers

314