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.
Sprache
Verlagsort
Verlagsgruppe
Elsevier Science Publishing Co Inc
Zielgruppe
Produkt-Hinweis
Broschur/Paperback
Klebebindung
Illustrationen
80 illustrations (30 in full color); Illustrations
Maße
Höhe: 235 mm
Breite: 191 mm
ISBN-13
978-0-12-822518-9 (9780128225189)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Arman Kilic, MD is Professor and Chief of Cardiothoracic Surgery and Chief of the Heart and Vascular Integrated Center of Clinical Excellence at the Medical University of South Carolina. He is the John Kratz Endowed Chair in Cardiac Surgery and has published over 350 peer reviewed manuscripts, has served as Principal Investigator on several clinical trials, and is a regularly invited national and international speaker on AI and machine learning in cardiovascular healthcare. He is a member of multiple editorial boards and has received several major extramural grants in AI.
Herausgeber*in
Professor and Chief of Cardiothoracic Surgery and Chief of the Heart and Vascular Integrated Center of Clinical Excellence. Medical University, South Carolina
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
