AI IN CLINICAL MEDICINE An essential overview of the application of artificial intelligence in clinical medicine
AI in Clinical Medicine: A Practical Guide for Healthcare Professionals is the definitive reference book for the emerging and exciting use of AI throughout clinical medicine. AI in Clinical Medicine: A Practical Guide for Healthcare Professionals is divided into four sections. Section 1 provides readers with the basic vocabulary that they require, a framework for AI, and highlights the importance of robust AI training for physicians. Section 2 reviews foundational ideas and concepts, including the history of AI. Section 3 explores how AI is applied to specific disciplines. Section 4 describes emerging trends, and applications of AI in medicine in the future.
Readers will find that this book:
Describes where AI is currently being used to change practice, and provides successful cases of AI approaches in specific medical domains.
Dives into the actual implementation of AI in the healthcare setting, and addresses reimbursement, workforce, and many other practical issues.
Addresses some of the unique challenges associated with AI in clinical medicine including ethical issues, as well as regulatory and privacy concerns.
Includes bulleted lists of learning objectives, key insights, clinical vignettes, brief examples of where AI is successfully deployed, and examples of potential problematic uses of AI and possible risks.
From radiology, to pathology, dermatology, endoscopy, robotics, virtual reality, and more, AI in Clinical Medicine: A Practical Guide for Healthcare Professionals explores all recent state-of-the-art developments in the field. It is an essential resource for a general medical audience across all disciplines, from students to clinicians, academics to policy makers.
Edited by:
Michael F. Byrne (University of British Columbia and Satisfai Health Canada),
Nasim Parsa (Satisfai Health,
Canada),
Alexandra T. Greenhill,
Daljeet Chahal (University of British Columbia,
Canada),
Omer Ahmad (University College London,
UK)
Imprint: Wiley-Blackwell
Country of Publication: United Kingdom
Dimensions:
Height: 259mm,
Width: 185mm,
Spine: 36mm
Weight: 1.406kg
ISBN: 9781119790648
ISBN 10: 1119790646
Pages: 592
Publication Date: 12 May 2023
Audience:
Professional and scholarly
,
Undergraduate
Format: Hardback
Publisher's Status: Active
List of Contributors xii Foreword xxiv Preface xxvi Michael Byrne Acknowledgements xxx Relevant AI Terms xxxii About the Companion Website xxxvi SECTION I Overview of Medical AI: The What, the Why, and the How 1 1 An Introduction to AI for Non-Experts 3 Sharib Ali and Michael Byrne 2 General Framework for Using AI in Clinical Practice 13 Judy L Barkal, Jack W Stockert, Jesse M Ehrenfeld, Charles E Aunger, and Lawrence K Cohen 3 AI and Medical Education 27 Alexandra T Greenhill SECTION II AI Foundations 39 4 History of AI in Clinical Medicine 41 Isaak Kavasidis, Federica Proietto Salanitri, Simone Palazzo, and Concetto Spampinato 5 History, Core Concepts, and Role of AI in Clinical Medicine 49 Christoph Palm 6 Building Blocks of AI 56 Ulas Bagci, Ismail Irmakci, Ugur Demir, and Elif Keles 7 Expert Systems for Interpretable Decisions in the Clinical Domain 66 Syed Muhammad Anwar 8 The Role of Natural Language Processing in Intelligence-Based Medicine 73 Maryam Panahiazar, Nolan Chen, Ramin E Beygui, and Dexter Hadley SECTION III AI Applied to Clinical Medicine 81 Frontline Care Specialties 9 AI in Primary Care, Preventative Medicine, and Triage 83 Yasmin Abedin, Omer F Ahmad, and Junaid Bajwa 10 Do It Yourself: Wearable Sensors and AI for Self-Assessment of Mental Health 94 Harish RaviPrakash and Syed Muhammad Anwar 11 AI in Dentistry 104 Lyudmila Tuzova, Dmitry Tuzoff, and L Eric Pulver 12 AI in Emergency Medicine 117 Jonathon Stewart, Adrian Goudie, Juan Lu, and Girish Dwivedi Medical Specialties 13 AI in Respirology and Bronchoscopy 129 Kevin Deasy, Henri Colt, and Marcus Kennedy 14 AI in Cardiology and Cardiac Surgery 144 Lin Gu 15 AI in the Intensive Care Unit 154 Dipayan Chaudhuri and Sandeep S Kohli 16 AI in Dermatology 165 Albert T Young, Jennifer Y Chen, Abhishek Bhattarcharya, and Maria L Wei 17 Artificial Intelligence in Gastroenterology 176 Trent Walradt and Tyler M Berzin 18 AI in Haematology 184 Paulina B Szklanna, Luisa Weiss, Brian Mac Namee, Rehman Faryal, Barry Kevane, Fionnuala Ní Áinle, and Patricia B Maguire 19 AI and Infectious Diseases 192 Alanna Ebigbo and Helmut Messmann 20 AI in Precision Medicine: The Way Forward 200 Prasun J Mishra 21 AI in Paediatrics 210 Darren Gates and Iain Hennessey 22 AI Applications in Rheumatology 219 Sarah Quidwai, Colm Kirby, and Grainne Murphy Surgical Specialties 23 Perspectives on AI in Anaesthesiology 228 Vesela Kovacheva 24 AI in Ear, Nose, and Throat 233 Jesús Rogel-Salazar and Krishan Ramdoo 25 AI in Obstetrics and Gynaecology 239 Sam Mathewlynn and Lucy Mackillop 26 AI in Ophthalmology 253 Nima John Ghadiri 27 AI in Orthopaedic Surgery 266 David Burns, Aazad Abbas, Jay Toor, and Michael Hardisty 28 AI in Surgery 282 Jesutofunmi A Omiye, Akshay Swaminathan, and Elsie G Ross 29 AI in Urological Oncology: Prostate Cancer Diagnosis with Magnetic Resonance Imaging 298 Sherif Mehralivand and Baris Turkbey Diagnostic Specialties 30 AI in Pathology 307 Stephanie Harmon and Kevin Ma 31 Introduction to AI in Radiology 318 Shu Min Yu and Amarpreet Mahil 32 Clinical Applications of AI in Diagnostic Imaging 321 Mohammed F Mohammed, Savvas Nicolaou, and Adnan Sheikh 33 AI for Workflow Enhancement in Radiology 337 Sabeena Jalal, Jason Yao, Savvas Nicolaou, and Adnan Sheikh 34 AI for Medical Image Processing: Improving Quality, Accessibility, and Safety 350 Leonid L Chepelev, Savvas Nicolaou, and Adnan Sheikh 35 Future Developments and Assimilation of AI in Radiology 365 Aakanksha Agarwal and Timothy É Murray SECTION IV Policy Issues, Practical Implementation, and Future Perspectives in Medical AI 377 AI Regulation, Privacy, Law 36 Medical Device AI Regulatory Expectations 379 Vesna Janic, Helen Simons, and Taimoor Khan 37 Privacy Laws in the USA, Europe, and South Africa 395 Sara Gerke 38 AI-Enabled Consumer-Facing Health Technology 407 Alexandra T Greenhill Ethics, Equity, Bias 39 Biases in Machine Learning in Healthcare 426 Dora Huang, Leo Anthony Celi, and Zachary O'Brien 40 'Designing' Ethics into AI: Ensuring Equality, Equity, and Accessibility 437 Lisa Murphy Design and Implementation 41 Making AI Work: Designing and Evaluating AI Systems in Healthcare 448 Niels van Berkel 42 Demonstrating Clinical Impact for AI Interventions: Importance of Robust Evaluation and Standardized Reporting 459 Gagandeep Sachdeva, Diana Han, Pearse A Keane, Alastair K Denniston, and Xiaoxuan Liu 43 The Importance and Benefits of Implementing Modern Data Infrastructure for Video-Based Medicine 469 Matt Schwartz and Ian Strug The Way Forward 44 AI and the Evolution of the Patient--Physician Relationship 478 Judy L Barkal, Jack W Stockert, Jesse M Ehrenfeld, and Lawrence K Cohen 45 Virtual Care and AI: The Whole Is Greater Than the Sum of Its Parts 488 Junaid Kalia 46 Summing It All Up: Evaluation, Integration, and Future Directions for AI in Clinical Medicine 498 Mark A Shapiro and Marty Tenenbaum 47 A Glimpse into the Future: AI, Digital Humans, and the Metaverse -- Opportunities and Challenges for Life Sciences in Immersive Ecologies 521 Siddharthan Surveswaran and Lakshmi Deshpande Index 528
Dr. Michael F.Byrne, lead editor, is a Clinical Professor of Medicine at the University of British Columbia, and is also CEO and founder of Satisfai Health, a leading provider of AI solutions in Gastroenterology. He is in great demand as a speaker and thought leader on the international medical AI circuit. Dr. Nasim Parsa is a gastroenterologist and clinical researcher with interest in patient outcomes and meaningful implementation of AI in practice. She is also the Vice President of Medical Affairs at Satisfai Health. Dr. Alexandra T. Greenhill is one of the leading physicians in healthinnovation, founder, advisor and board member of some of the best digital health focused organizations on a mission to accelerate the future of health. Dr. Daljeet Chahal is a board-certified gastroenterologist and clinical researcher who recently finished advanced hepatology training at the Mount Sinai Hospital in New York City. He has returned to Vancouver to practice medicine at the University of British Columbia, and hopes to incorporate machine learning technologies into his future clinical, research, and business endeavors. Dr. Omer Ahmad is a gastroenterologist and senior clinical translational research scientist at University College London. He has successfully co-developed AI software that is being used in routine clinical practice, and published international initiatives related to the effective implementation of AI solutions. Dr. Ulas Bagci is an Associate Professor at Northwestern University’s Radiology, ECE, and Biomedical Engineering Departments in Chicago, and Courtesy Professor at the Center for Research in Computer Vision (CRCV), Department of Computer Science, at the University of Central Florida (UCF).
