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
