Artificial Intelligence and Machine Learning in Healthcare
- 1st Edition - September 1, 2025
- Imprint: Academic Press
- Editor: Arman Kilic
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 2 2 5 1 8 - 9
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 2 2 5 1 9 - 6
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 artifi… Read more
Purchase options
Institutional subscription on ScienceDirect
Request a sales quoteArtificial 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.
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.
- Provides an overview of AI and ML to the medical practitioner who may not be well versed in these fields
- Encompasses a thorough review of what has been accomplished and demonstrated recently in the fields of AI and ML in healthcare
- Discusses the future of AI and ML in healthcare, with a review of possible wearable technology and software and how they may be used for medical care
Clinicians, medical doctors, bioinformaticians, graduate students
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
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
- Edition: 1
- Published: September 1, 2025
- Imprint: Academic Press
- No. of pages: 300
- Language: English
- Paperback ISBN: 9780128225189
- eBook ISBN: 9780128225196
AK
Arman Kilic
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.
Affiliations and expertise
Director, Surgical Quality and Analytics for University of Pittsburgh Division of Cardiac Surgery, USA