Artificial Intelligence in Healthcare

Artificial Intelligence in Healthcare

1st Edition - June 21, 2020
This is the Latest Edition
  • Editors: Adam Bohr, Kaveh Memarzadeh
  • eBook ISBN: 9780128184394
  • Paperback ISBN: 9780128184387

Purchase options

Purchase options
DRM-free (EPub, Mobi, PDF)
Available
Sales tax will be calculated at check-out

Institutional Subscription

Free Global Shipping
No minimum order

Description

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction toartificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare.

Key Features

  • Highlights different data techniques in healthcare data analysis, including machine learning and data mining
  • Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks
  • Includes applications and case studies across all areas of AI in healthcare data

Readership

Researchers, graduate students, and practitioners in computer science, data science, bioinformatics, health informatics, biomedical engineering, clinical engineering, healthcare professionals interested in the applications of AI in healthcare data. This book is written for a broad audience and specifically those interested in the healthcare applications of Artificial Intelligence including clinicians, health and life science professionals, policy makers, business leaders, university students and patients.

Table of Contents

  • List of contributors xi

    About the editors xiii

    Biographies xv

    Preface xxi

    Introduction xxiii

    1. Current healthcare, big data, and machine learning 1

    Adam Bohr and Kaveh Memarzadeh

    1.1 Current healthcare practice 1

    1.2 Value-based treatments and healthcare services 5

    1.3 Increasing data volumes in healthcare 10

    1.4 Analytics of healthcare data (machine learning and deep learning) 16

    1.5 Conclusions/summary 21

    References 22

    2. The rise of artificial intelligence in healthcare applications 25

    Adam Bohr and Kaveh Memarzadeh

    2.1 The new age of healthcare 25

    2.2 Precision medicine 28

    2.3 Artificial intelligence and medical visualization 33

    2.4 Intelligent personal health records 38

    2.5 Robotics and artificial intelligence-powered devices 43

    2.6 Ambient assisted living 46

    2.7 The artificial intelligence can see you now 50

    References 57

    3. Drug discovery and molecular modeling using artificial intelligence 61

    Henrik Bohr

    3.1 Introduction. The scope of artificial intelligence in drug discovery 61

    3.2 Various types of machine learning in artificial intelligence 64

    3.3 Molecular modeling and databases in artificial intelligence for drug

    molecules 70

    3.4 Computational mechanics ML methods in molecular modeling 72

    3.5 Drug characterization using isopotential surfaces 74

    3.6 Drug design for neuroreceptors using artificial neural network techniques 75

    3.7 Specific use of deep learning in drug design 78

    3.8 Possible future artificial intelligence development in drug design and

    development 80

    References 81

    4. Applications of artificial intelligence in drug delivery and pharmaceutical development 85

    Stefano Colombo

    4.1 The evolving pharmaceutical field 85

    4.2 Drug delivery and nanotechnology 89

    4.3 Quality-by-design R&D 92

    4.4 Artificial intelligence in drug delivery modeling 95

    4.5 Artificial intelligence application in pharmaceutical product R&D 98

    4.6 Landscape of AI implementation in the drug delivery industry 109

    4.7 Conclusion: the way forward 110

    References 111

    5. Cancer diagnostics and treatment decisions using artificial intelligence 117

    Reza Mirnezami

    5.1 Background 117

    5.2 Artificial intelligence, machine learning, and deep learning in cancer 119

    5.3 Artificial intelligence to determine cancer susceptibility 122

    5.4 Artificial intelligence for enhanced cancer diagnosis and staging 125

    5.5 Artificial intelligence to predict cancer treatment response 127

    5.6 Artificial intelligence to predict cancer recurrence and survival 130

    5.7 Artificial intelligence for personalized cancer pharmacotherapy 133

    5.8 How will artificial intelligence affect ethical practices and patients? 136

    5.9 Concluding remarks 137

    References 139

    6. Artificial intelligence for medical imaging 143

    Khanhvi Tran, Johan Peter Bøtker, Arash Aframian and Kaveh Memarzadeh

    6.1 Introduction 143

    6.2 Outputs of artificial intelligence in radiology/medical imaging 144

    6.3 Using artificial intelligence in radiology and overcoming its hurdles 146

    6.4 X-rays and artificial intelligence in medical imaging—case 1 (Zebra medical

    vision) 151

    6.5 Ultrasound and artificial intelligence in medical imaging—case 2

    (Butterfly iQ) 156

    6.6 Application of artificial intelligence in medical imaging—case 3 (Arterys) 158

    6.7 Perspectives 160

    References 161

    7. Medical devices and artificial intelligence 163

    Arash Aframian, Farhad Iranpour and Justin Cobb

    7.1 Introduction 163

    7.2 The development of artificial intelligence in medical devices 163

    7.3 Limitations of artificial intelligence in medical devices 171

    7.4 The future frontiers of artificial intelligence in medical devices 172

    References 174

    8. Artificial intelligence assisted surgery 179

    Elan Witkowski and Thomas Ward

    8.1 Introduction 179

    8.2 Preoperative 179

    8.3 Intraoperative 185

    8.4 Postoperative 193

    8.5 Conclusion 196

    References 197

    Further reading 202

    9. Remote patient monitoring using artificial intelligence 203

    Zineb Jeddi and Adam Bohr

    9.1 Introduction to remote patient monitoring 203

    9.2 Deploying patient monitoring 205

    9.3 The role of artificial intelligence in remote patient monitoring 209

    9.4 Diabetes prediction and monitoring using artificial intelligence 219

    9.5 Cardiac monitoring using artificial intelligence 221

    9.6 Neural applications of artificial intelligence and remote patient

    monitoring 224

    9.7 Conclusions 229

    References 230

    10. Security, privacy, and information-sharing aspects of healthcare

    artificial intelligence 235

    Jakub P. Hlávka

    10.1 Introduction to digital security and privacy 235

    10.2 Security and privacy concerns in healthcare artificial intelligence 237

    10.3 Artificial intelligence’s risks and opportunities for data privacy 245

    10.4 Addressing threats to health systems and data in the artificial

    intelligence age 253

    10.5 Defining optimal responses to security, privacy, and information-sharing

    challenges in healthcare artificial intelligence 255

    10.6 Conclusions 263

    Acknowledgements 264

    References 265

    11. The impact of artificial intelligence on healthcare insurances 271

    Rajeev Dutt

    11.1 Overview of the global health insurance industry 271

    11.2 Key challenges facing the health insurance industry 272

    11.3 The application of artificial intelligence in the health insurance industry 274

    11.4 Case studies 280

    11.5 Moral, ethical, and regulatory concerns regarding the use of artificial

    intelligence 280

    11.6 The limitations of artificial intelligence 282

    11.7 The future of artificial intelligence in the health insurance industry 289

    References 290

    12. Ethical and legal challenges of artificial intelligence-driven

    healthcare 295

    Sara Gerke, Timo Minssen and Glenn Cohen

    12.1 Understanding “artificial intelligence” 296

    12.2 Trends and strategies 296

    12.3 Ethical challenges 300

    12.4 Legal challenges 306

    12.5 Conclusion 327

    Acknowledgements 328

    References 329

    Concluding remarks 337

    Index 339

Product details

  • No. of pages: 378
  • Language: English
  • Copyright: © Academic Press 2020
  • Published: June 21, 2020
  • Imprint: Academic Press
  • eBook ISBN: 9780128184394
  • Paperback ISBN: 9780128184387

About the Editors

Adam Bohr

Adam Bohr, PhD is the CEO and co-founder of Sonohaler, an mhealth and medical device company focused on asthma management using acoustic signals and machine learning tools. He is also a co-founder of Zerion ApS, a pharmaceutical company aspiring to transform the pharmaceutical landscape for formulation of poorly soluble drugs. Previously, he was employed as assistant professor at the Department of Pharmacy, University of Copenhagen where he was doing research on drug implants, nanomedicine and microfluidic technology and teaching pharmaceutical technology subjects. He has published more than 45 peer reviewed academic papers and book chapters and has a PhD in Biomedical Engineering from University College London. He is a health futurist and a healthcare AI proponent with a passion for patient centered healthcare technologies.

Affiliations and Expertise

Adam Bohr, PhD is the CEO and Co-founder of Sonohaler, Copenhagen, Denmark

Kaveh Memarzadeh

Kaveh Memarzadeh, PhD is currently a Commercial Field Application Scientist at ChemoMetec, a biotechnology company that innovates in the field of automated cell cytometry. He oversaw research management and communications at Orthopaedic Research UK (ORUK), a UK based medical charity that funds projects into the betterment and improvement of human movement and augmentation. He has published numerous peer-reviewed academic papers and has a PhD in nanotechnology, biomaterials and microbiology. He is also a visiting lecturer at University College London, teaching on a range of topics from the future of prosthetics/bionics to utilization of nanotechnology for antimicrobial bone implants. In his spare time, he reads, paints, builds his own gaming computers and utilizes the power of social media to share his passion for nature with hundreds of thousands of people.

Affiliations and Expertise

Kaveh Memarzadeh, PhD is currently a Commercial Field Application Scientist at ChemoMetec, Lillerød, Denmark.

Latest reviews

(Total rating for all reviews)

  • James P. Thu Jun 25 2020

    Fantastic overview

    A great overview of current issues in healthcare AI, ranging from drug discover and clinical advances to privacy and ethics. Highly recommend.