Artificial Intelligence and Machine Learning in Healthcare

Artificial Intelligence and Machine Learning in Healthcare discusses the potential of groundbreaking technologies on the delivery of care. A lot have been said about how artificial intelligence and machine learning can improve healthcare, however there are still many doubts and concerns among health professionals, all of which are addressed in this book. Sections cover History and Basic Overview of AI and ML, with differentiation of supervised, unsupervised and deep learning, Applications of AI and ML in Healthcare, The Future of Healthcare with AI, Challenges to Adopting AI in Healthcare, and ethics and legal processes for implementation.

This book is a valuable resource for bioinformaticians, clinicians, graduate students and several members of biomedical field who needs to get up to speed on the revolutionary role of AI and Machine Learning in healthcare.

Part I: History and Basic Overview of AI and ML
1. Historical Background of AI and ML
2. Introduction to AI and ML Techniques
3. Supervised Learning
4. Unsupervised Learning
5. Deep Learning

Part II: Applications of AI and ML in Healthcare
6. Primary Care
7. Ophthalmology
8. Oncology
9. Radiology
10. Emergency Medicine
11. Intensive Care Unit
12. Cardiovascular Medicine and Surgery
13. Data Extraction and Quality Control in the Electronic Health Record

Part III: The Future of Healthcare with AI
14. Wearable Technology
15. Software for Automated Interpretation of Medical Imaging
16. Software for Clinical Decision Support
17. The Impact of AI on Healthcare Finance

Part IV: Challenges to Adopting AI in Healthcare
18. Ethical Challenges
19. Legal Processes Required to Implement AI in Healthcare
20. Gaining Patients’ Trust in AI for their Healthcare

Arman Kilic, MD, is Director, Surgical Quality and Analytics for University of Pittsburgh Division of Cardiac Surgery, and Co-Director, Center for Cardiovascular Outcomes and Innovation, University of Pittsburgh Medical Center. Dr. Kilic works on a national task force for artificial intelligence and machine learning in cardiac surgery and has extensive collaboration with internationally renowned machine learning experts at Carnegie Mellon University, the #1 ranked machine learning program according to U.S. News & World Report. He has a vast network of national and international colleagues who can collaborate on this project and contribute as authors of chapters. Dr. Kilic has 158 peer-reviewed publications, 14 book chapters, and 111 meeting presentations.