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AI in Clinical Medicine
A Practical Guide for Healthcare Professionals
Michael F. Byrne (Edited by), Nasim Parsa (Edited by), Alexandra T. Greenhill (Edited by), Daljeet Chahal (Edited by), Omer Ahmad (Edited by), Ulas Bagci (Edited by)
9781119790648, Wiley
Hardback, published 12 May 2023
592 pages
25.9 x 18.5 x 3.6 cm, 1.406 kg
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: 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.
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 2 General Framework for Using AI in Clinical Practice 13 3 AI and Medical Education 27 SECTION II AI Foundations 39 4 History of AI in Clinical Medicine 41 5 History, Core Concepts, and Role of AI in Clinical Medicine 49 6 Building Blocks of AI 56 7 Expert Systems for Interpretable Decisions in the Clinical Domain 66 8 The Role of Natural Language Processing in Intelligence-Based Medicine 73 SECTION III AI Applied to Clinical Medicine 81 Frontline Care Specialties 9 AI in Primary Care, Preventative Medicine, and Triage 83 10 Do It Yourself: Wearable Sensors and AI for Self-Assessment of Mental Health 94 11 AI in Dentistry 104 12 AI in Emergency Medicine 117 Medical Specialties 13 AI in Respirology and Bronchoscopy 129 14 AI in Cardiology and Cardiac Surgery 144 15 AI in the Intensive Care Unit 154 16 AI in Dermatology 165 17 Artificial Intelligence in Gastroenterology 176 18 AI in Haematology 184 19 AI and Infectious Diseases 192 20 AI in Precision Medicine: The Way Forward 200 21 AI in Paediatrics 210 22 AI Applications in Rheumatology 219 Surgical Specialties 23 Perspectives on AI in Anaesthesiology 228 24 AI in Ear, Nose, and Throat 233 25 AI in Obstetrics and Gynaecology 239 26 AI in Ophthalmology 253 27 AI in Orthopaedic Surgery 266 28 AI in Surgery 282 29 AI in Urological Oncology: Prostate Cancer Diagnosis with Magnetic Resonance Imaging 298 Diagnostic Specialties 30 AI in Pathology 307 31 Introduction to AI in Radiology 318 32 Clinical Applications of AI in Diagnostic Imaging 321 33 AI for Workflow Enhancement in Radiology 337 34 AI for Medical Image Processing: Improving Quality, Accessibility, and Safety 350 35 Future Developments and Assimilation of AI in Radiology 365 SECTION IV Policy Issues, Practical Implementation, and Future Perspectives in Medical AI 377 AI Regulation, Privacy, Law 36 Medical Device AI Regulatory Expectations 379 37 Privacy Laws in the USA, Europe, and South Africa 395 38 AI-Enabled Consumer-Facing Health Technology 407 Ethics, Equity, Bias 39 Biases in Machine Learning in Healthcare 426 40 'Designing' Ethics into AI: Ensuring Equality, Equity, and Accessibility 437 Design and Implementation 41 Making AI Work: Designing and Evaluating AI Systems in Healthcare 448 42 Demonstrating Clinical Impact for AI Interventions: Importance of Robust Evaluation and Standardized Reporting 459 43 The Importance and Benefits of Implementing Modern Data Infrastructure for Video-Based Medicine 469 The Way Forward 44 AI and the Evolution of the Patient--Physician Relationship 478 45 Virtual Care and AI: The Whole Is Greater Than the Sum of Its Parts 488 46 Summing It All Up: Evaluation, Integration, and Future Directions for AI in Clinical Medicine 498 47 A Glimpse into the Future: AI, Digital Humans, and the Metaverse -- Opportunities and Challenges for Life Sciences in Immersive Ecologies 521 Index 528
Sharib Ali and Michael Byrne
Judy L Barkal, Jack W Stockert, Jesse M Ehrenfeld, Charles E Aunger, and Lawrence K Cohen
Alexandra T Greenhill
Isaak Kavasidis, Federica Proietto Salanitri, Simone Palazzo, and Concetto Spampinato
Christoph Palm
Ulas Bagci, Ismail Irmakci, Ugur Demir, and Elif Keles
Syed Muhammad Anwar
Maryam Panahiazar, Nolan Chen, Ramin E Beygui, and Dexter Hadley
Yasmin Abedin, Omer F Ahmad, and Junaid Bajwa
Harish RaviPrakash and Syed Muhammad Anwar
Lyudmila Tuzova, Dmitry Tuzoff, and L Eric Pulver
Jonathon Stewart, Adrian Goudie, Juan Lu, and Girish Dwivedi
Kevin Deasy, Henri Colt, and Marcus Kennedy
Lin Gu
Dipayan Chaudhuri and Sandeep S Kohli
Albert T Young, Jennifer Y Chen, Abhishek Bhattarcharya, and Maria L Wei
Trent Walradt and Tyler M Berzin
Paulina B Szklanna, Luisa Weiss, Brian Mac Namee, Rehman Faryal, Barry Kevane, Fionnuala Ní Áinle, and Patricia B Maguire
Alanna Ebigbo and Helmut Messmann
Prasun J Mishra
Darren Gates and Iain Hennessey
Sarah Quidwai, Colm Kirby, and Grainne Murphy
Vesela Kovacheva
Jesús Rogel-Salazar and Krishan Ramdoo
Sam Mathewlynn and Lucy Mackillop
Nima John Ghadiri
David Burns, Aazad Abbas, Jay Toor, and Michael Hardisty
Jesutofunmi A Omiye, Akshay Swaminathan, and Elsie G Ross
Sherif Mehralivand and Baris Turkbey
Stephanie Harmon and Kevin Ma
Shu Min Yu and Amarpreet Mahil
Mohammed F Mohammed, Savvas Nicolaou, and Adnan Sheikh
Sabeena Jalal, Jason Yao, Savvas Nicolaou, and Adnan Sheikh
Leonid L Chepelev, Savvas Nicolaou, and Adnan Sheikh
Aakanksha Agarwal and Timothy É Murray
Vesna Janic, Helen Simons, and Taimoor Khan
Sara Gerke
Alexandra T Greenhill
Dora Huang, Leo Anthony Celi, and Zachary O'Brien
Lisa Murphy
Niels van Berkel
Gagandeep Sachdeva, Diana Han, Pearse A Keane, Alastair K Denniston, and Xiaoxuan Liu
Matt Schwartz and Ian Strug
Judy L Barkal, Jack W Stockert, Jesse M Ehrenfeld, and Lawrence K Cohen
Junaid Kalia
Mark A Shapiro and Marty Tenenbaum
Siddharthan Surveswaran and Lakshmi Deshpande
Subject Areas: Clinical & internal medicine [MJ]
