1st Edition

Translational Application of Artificial Intelligence in Healthcare - A Textbook

Edited By Sandeep Reddy Copyright 2024
    144 Pages 19 B/W Illustrations
    by Chapman & Hall

    144 Pages 19 B/W Illustrations
    by Chapman & Hall

    144 Pages 19 B/W Illustrations
    by Chapman & Hall

    In the era of 'Algorithmic Medicine', the integration of Artificial Intelligence (AI) in healthcare holds immense potential to address critical challenges faced by the industry. 

    Drawing upon the expertise and experience of the authors in medicine, data science, medical informatics, administration, and entrepreneurship, this textbook goes beyond theoretical discussions to outline practical steps for transitioning AI from the experimental phase to real-time clinical integration. Using the Translational Science methodology, each chapter of the book concisely and clearly addresses the key issues associated with AI implementation in healthcare. Covering technical, clinical, ethical, regulatory, and legal considerations, the authors present evidence-based solutions and frameworks to overcome these challenges.

    Engaging case studies and a literature review of peer-reviewed studies and official documents from reputed organizations provide a balanced perspective, bridging the gap between AI research and actual clinical practice.

    1. An Introduction to Artificial Intelligence, Sandeep Reddy 2. Applications of AI in Healthcare, Joe Zhang and Stephen Whebell 3. The Need for AI in Healthcare, Vince Madai 4. Technical Issues in Implementing AI in Healthcare, Sonika Tyagi 5. Barriers and Solutions to Adoption of AI in Healthcare, Piyush Mathur and Bart Geerts 6. Ethics, Regulation and Legal Issues of AI in Healthcare, Sandra Johnson and Sandeep Reddy 7. Translational Challenges of Implementing AI in Healthcare: Solutions and Opportunities, Dwarikanath Mahapatra and Sandeep Reddy 8. The Translational Application of AI in Healthcare, Piyush Mathur and Frank Papay


    Sandeep Reddy is an Artificial Intelligence (AI) in healthcare researcher based at the Deakin School of Medicine, as well as being the founder/chairman of Medi-AI, a healthcare-focused AI entity. He is also a certified health informatician and World Health Organization–recognised digital health expert. He has a medical and healthcare management background and has completed machine learning/health informatics training from various sources. He is currently engaged in research about the safety, quality and explainability of the application of AI in healthcare delivery, in addition to developing AI models to treat and manage chronic diseases. He has also authored several articles and books about the use of AI in medicine. Further, he has set up local and international forums to promote the use of AI in healthcare and sits on various international committees which focus on this issue.

    This book provides a very readable introduction into our current understanding of all these issues and affords the opportunity for non-AI experts to appreciate how AI can improve clinical care while being made aware of its current limitations and how these may be overcome.
    Professor Ian Scott, Director of| Internal Medicine and Clinical Epidemiology | Princess Alexandra Hospital; Professor of Medicine, University of Queensland

    This book is essential because it begins to delineate that pathway to implementation, guiding readers to consider issues beyond predictive performance as they develop the AI applications of the future.Professor Wendy W. Chapman, Director of the Centre for Digital Transformation of Health, University of Melbourne

    Advances in technology have always been a driver for improved delivery of healthcare. The application of AI in healthcare has the potential to be the driver that will lead to a more effective and efficient healthcare delivery system. This book provides a very lucid overview of the potential applications and benefits, and also addresses the potential challenges in the adoption of AI in healthcare. A sound grounding and understanding of the potential applications of AI will empower clinicians and scientists to adapt and hopefully expand the scope of its application.

    Girish Nair, Director of Functional Neurosurgery, The Royal Melbourne Hospital and Head of Unit of Neurosurgery, Western Health

    "The hardest part of innovation is not invention but the implementation of new technology. Moreover, clinical medicine, where one mistake may affect the mortality of innumerable people, is one of the most difficult fields to implement emerging technologies. Although it won't teach us the best racing line for the podium, this book shows us the starting grid of the circuit for the ones who want to achieve innovation."

    Tomohiro Kuroda, CIO of Kyoto University Hospital, Director of the Center for Digital Transformation of Healthcare, Professor of Graduate School of Medicine, Professor of Graduate School of Informatics, Kyoto University