Intelligence-Based Healthcare

An Essential Guide with Case Studies of Artificial Intelligence for the Healthcare Leader and Provider
Erscheinungsjahr 2026
ISBN: 978-0-443-33933-2
Verlag: Elsevier Science

Buch, Englisch, 350 Seiten, Format (B × H): 191 mm x 235 mm

Intelligence-Based Healthcare: An Essential Guide with Case Studies of Artificial Intelligence for the Healthcare Leader and Provider is an essential guide with an introduction to data science and artificial intelligence to provide the reader with a quick orientation and education on AI in healthcare. This book also offers a framework for success in planning, deployment, implementation, and evaluation of AI models in healthcare. In 25 chapters, Intelligence-Based Healthcare: An Essential Guide with Case Studies of Artificial Intelligence for the Healthcare Leader and Provider both introduces the reader to artificial in medicine and healthcare, and AI concepts. To render AI more understandable and relatable to the reader, case studies are used as a learning strategy to illustrate the aforementioned AI concepts. The cases implement AI in solving a very specific problem, clinical or operational, in clinical medicine or healthcare. Both cases that illustrate successful implementation of AI as unsuccessful application cases with important lessons learned are included. Each chapter can be read independently and therefore the book is a valuable resource for researchers, health professionals, postgraduate students, post doc researchers and faculty members in the fields of artificial intelligence in medicine and healthcare, and all those who wish to broaden their knowledge in the allied field.

Autoren/Hrsg.

Chang, Anthony

Limon, Alfonso

Gascon, Gregg M

Fachgebiete

• Naturwissenschaften Biowissenschaften Biowissenschaften

Inhaltsverzeichnis

1. Introduction
2. Brief History of Artificial Intelligence
3. Reflection and Update on AI in Medicine and Healthcare
4. Topics
5. Definitions
6. Machine Learning Supervised, Unsupervised, Semi- and Self-Supervised
7. Deep Learning Neural Nets and Transformers
8. Reinforcement Learning
9. Generative Artificial Intelligence
10. Natural Language Processing
11. Cognitive Computing
12. Robotic Process Automation
13. Regulation, Ethics, Adoption, and Legal (REAL) Issues
14. Implementation Science
15. Miscellaneous Topics
16. Why Adoption of AI in Healthcare Has Been Challenging
17. Framework for Successful Adoption of AI in Healthcare
18. How to Pursue a Basic to Advanced Education on Artificial Intelligence
19. How to Build Data, IT, and AI Infrastructure
20. How to Start a Center of Artificial Intelligence
21. Future of Artificial Intelligence and Health
22. Compendium
23. Glossary
24. Top 100 Articles of AI in Healthcare
25. Book Recommendations

Über Autor(innen)

Limon, Alfonso
Alfonso Limon, Ph.D., is a principal at Oneirix, a consulting company developing market-leading technologies in computational intelligence for med-tech. Before joining Oneirix, Dr. Limon served as Director of Research at Intersection Medical, leading the development of algorithms for decision support systems to manage congestive heart failure. Before his work in industry, Dr. Limon was a Visiting Professor of Mathematics at Pomona College and a post-doctoral fellow at Harvey Mudd College in the math department and holds several impedance spectroscopy patents. Alfonso is part of the American Board of Artificial Intelligence in Medicine, an Associate Editor of Intelligence-Based Medicine, and the Computational Science Research Center Board Chair at SDSU.

Chang, Anthony
Anthony Chang, MD, is a Professor, Department of Pathology, University of Chicago with a specialty in renal pathology. His research interests include the role of B and plasma cells in lupus nephritis and transplant rejection. He is past president of the Renal Pathology Society (2017) and Chicago Pathology Society (2011-2013). He has taught more than 30 educational courses at the annual meetings for the American Society Clinical Pathology, College of American Pathologists, US & Canadian Academy of Pathology, American Society of Nephrology, American College of Rheumatology, and American Urological Association.