Transforming Healthcare Using Artificial Intelligence provides insights executing healthcare transformation through artificial intelligence, deploying health technology at scale, technology research, development and adoption and, interactions with leading clinicians and healthcare administrators from around the world. With a strong focus on what is most needed to transform healthcare systems to improve patient outcomes while managing costs, and how selected use of artificial intelligence can dovetail with those needs, this book also contrast this with a “tech push” approach where innovations are made, and it is then seen how they might be used in the practice of healthcare. In 14 chapters "Transforming Healthcare Using Artificial Intelligence" lays out the most urgent challenges facing both the patient and the provider. For patients, these include patient lifestyle, patient self-empowerment, adherence, knowledge, and behaviour change. Meanwhile, for clinicians the challenges are information overload, time scarcity, rapidly changing guidelines and care protocols, care quality, as well as “feeding the beast” of EMRs and insurance documentation It explains recent AI breakthroughs and then critically evaluates the promise of AI and shows how it can be selectively and successfully deployed to alleviate these challenges. Illustrations are drawn from real deployments and scaling, and rigorous experimentation and evidence-gathering throws light on the best bets for AI in Healthcare. While innovation in this field is moving very fast, adoption is appropriately slowed by the need for assurances of patient safety, clinical trials and, in some cases, regulatory approvals. This book is a valuable resource for health professionals, scientists and researchers, health practitioners, students, and all those who wish to broaden their knowledge in the allied field.
Table of Contents
1. Introduction2. The healthcare enterprise and its most pressing current clinical and operational challenges
3. The challenges of the healthcare business model, and how AI could help:
4. The greatest burden of disease and cost-drivers: chronic diseases and their complications. How AI could result in a leap
5. Use-case Area 1 Medical Imaging: the vanguard of AI in Healthcare
6. Use-case Area 2 Lifestyle changes: the biggest lever
7. Use-case Area 3 Mental Health as a compelling area for hybrid AI approaches:
8. Use-case Area 4 Aging:
9. Generative AI, its promises and perils, and why we are just at the beginning:
10. The key to successful AI breakthroughs and scalable deployment: Data
11. How AI should be delivered and barriers to adoption:
12. Safety, Regulation and Ethics
13. How AI can transform care in emerging economies:
14. Conclusions Appendix: A basic tutorial and set of references on AI techniques.
