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.
1. Cover image - p. c 2. Title page - p. i 3. Copyright - p. ii 4. Contents - p. v 5. Contributors - p. ix 6. Chapter 1 A practical guide to machine learning applications and software - p. 1 7. Chapter 2 Artificial intelligence in primary care - p. 17 8. Chapter 3 Pediatric and neonatal care - p. 27 9. Chapter 4 Radiology - p. 37 10. Chapter 5 Emergency medicine and artificial intelligence - p. 61 11. Chapter 6 Artificial intelligence in critical care medicine - p. 69 12. Chapter 7 Cardiovascular medicine and surgery - p. 87 13. Chapter 8 Artificial intelligence in surgery - p. 99 14. Chapter 9 Neurology and machine learning - p. 115 15. Chapter 10 Applications in the electronic health record - p. 129 16. Chapter 11 Leveraging insurance claims data - p. 141 17. Chapter 12 Artificial intelligence and wearables - p. 159 18. Chapter 13 Machine learning and optimization for comprehensive upstream-to-downstream surgical scheduling and capacity planning - p. 179 19. Chapter 14 From potential to proof: How artificial intelligence in healthcare now delivers measurable return on investment—and why many companies risk falling behind - p. 197 20. Chapter 15 Legal processes required to implement artificial intelligence in healthcare - p. 213 21. Chapter 16 Artificial intelligence in medical education - p. 223 22. Index - p. 245
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.
1. Cover image - p. c 2. Title page - p. i 3. Copyright - p. ii 4. Contents - p. v 5. Contributors - p. ix 6. Chapter 1 A practical guide to machine learning applications and software - p. 1 7. Chapter 2 Artificial intelligence in primary care - p. 17 8. Chapter 3 Pediatric and neonatal care - p. 27 9. Chapter 4 Radiology - p. 37 10. Chapter 5 Emergency medicine and artificial intelligence - p. 61 11. Chapter 6 Artificial intelligence in critical care medicine - p. 69 12. Chapter 7 Cardiovascular medicine and surgery - p. 87 13. Chapter 8 Artificial intelligence in surgery - p. 99 14. Chapter 9 Neurology and machine learning - p. 115 15. Chapter 10 Applications in the electronic health record - p. 129 16. Chapter 11 Leveraging insurance claims data - p. 141 17. Chapter 12 Artificial intelligence and wearables - p. 159 18. Chapter 13 Machine learning and optimization for comprehensive upstream-to-downstream surgical scheduling and capacity planning - p. 179 19. Chapter 14 From potential to proof: How artificial intelligence in healthcare now delivers measurable return on investment—and why many companies risk falling behind - p. 197 20. Chapter 15 Legal processes required to implement artificial intelligence in healthcare - p. 213 21. Chapter 16 Artificial intelligence in medical education - p. 223 22. Index - p. 245
