Artificial Intelligence in Precision Health: From Concept to Applications provides a readily available resource to understand artificial intelligence and its real time applications in precision medicine in practice. Written by experts from different countries and with diverse background, the content encompasses accessible knowledge easily understandable for non-specialists in computer sciences. The book discusses topics such as cognitive computing and emotional intelligence, big data analysis, clinical decision support systems, deep learning, personal omics, digital health, predictive models, prediction of epidemics, drug discovery, precision nutrition and fitness. Additionally, there is a section dedicated to discuss and analyze AI products related to precision healthcare already available.
This book is a valuable source for clinicians, healthcare workers, and researchers from diverse areas of biomedical field who may or may not have computational background and want to learn more about the innovative field of artificial intelligence for precision health.
1. Cover image - p. page_i 2. Title page - p. page_i 3. Table of Contents - p. page_i 4. Copyright - p. page_iv 5. Dedication - p. page_v 6. Contributors - p. page_xix 7. Editor's biography - p. page_xxiii 8. Preface - p. page_xxv 9. Section I: Artificial intelligence technologies - p. page_xxvii 10. Chapter 1: Interpretable artificial intelligence: Closing the adoption gap in healthcare - p. page_xxvii 11. Chapter 2: Artificial intelligence methods in computer-aided diagnostic tools and decision support analytics for clinical informatics - p. page_29 12. Chapter 3: Deep learning in precision medicine - p. page_59 13. Chapter 4: Machine learning systems and precision medicine: A conceptual and experimental approach to single individual statistics - p. page_90 14. Chapter 5: Machine learning in digital health, recent trends, and ongoing challenges - p. page_119 15. Chapter 6: Data mining to transform clinical and translational research findings into precision health - p. page_148 16. Section II: Applications of artificial intelligence in precision health - p. page_173 17. Chapter 7: Predictive models in precision medicine - p. page_173 18. Chapter 8: Deep neural networks for phenotype prediction in rare diseases: Inclusion body myositis: A case study - p. page_188 19. Chapter 9: Artificial intelligence for management of patients with intracranial neoplasms - p. page_202 20. Chapter 10: Artificial intelligence to aid the detection of mood disorders - p. page_229 21. Chapter 11: Use of artificial intelligence in Alzheimer’s disease detection - p. page_255 22. Chapter 12: Artificial intelligence to predict atheroma plaque vulnerability - p. page_278 23. Chapter 13: Artificial intelligence in cardiovascular medicine: Applications in the diagnosis of infarction and prognosis of heart failure - p. page_312 24. Chapter 14: Artificial intelligence-based decision support systems for diabetes - p. page_328 25. Chapter 15: Clinical decision support systems to improve the diagnosis and management of respiratory diseases - p. page_357 26. Chapter 16: Artificial intelligence in neuro, head, and neck surgery - p. page_391 27. Chapter 17: Use of artificial intelligence in emergency medicine - p. page_404 28. Chapter 18: Use of artificial intelligence in infectious diseases - p. page_413 29. Chapter 19: Artificial intelligence techniques applied to patient care and monitoring - p. page_438 30. Chapter 20: Use of artificial intelligence in precision nutrition and fitness - p. page_464 31. Section III: Precision systems in practice - p. page_496 32. Chapter 21: Artificial intelligence in precision health: Systems in practice - p. page_496 33. Index - p. page_521
Artificial Intelligence in Precision Health: From Concept to Applications provides a readily available resource to understand artificial intelligence and its real time applications in precision medicine in practice. Written by experts from different countries and with diverse background, the content encompasses accessible knowledge easily understandable for non-specialists in computer sciences. The book discusses topics such as cognitive computing and emotional intelligence, big data analysis, clinical decision support systems, deep learning, personal omics, digital health, predictive models, prediction of epidemics, drug discovery, precision nutrition and fitness. Additionally, there is a section dedicated to discuss and analyze AI products related to precision healthcare already available.
This book is a valuable source for clinicians, healthcare workers, and researchers from diverse areas of biomedical field who may or may not have computational background and want to learn more about the innovative field of artificial intelligence for precision health.
1. Cover image - p. page_i 2. Title page - p. page_i 3. Table of Contents - p. page_i 4. Copyright - p. page_iv 5. Dedication - p. page_v 6. Contributors - p. page_xix 7. Editor's biography - p. page_xxiii 8. Preface - p. page_xxv 9. Section I: Artificial intelligence technologies - p. page_xxvii 10. Chapter 1: Interpretable artificial intelligence: Closing the adoption gap in healthcare - p. page_xxvii 11. Chapter 2: Artificial intelligence methods in computer-aided diagnostic tools and decision support analytics for clinical informatics - p. page_29 12. Chapter 3: Deep learning in precision medicine - p. page_59 13. Chapter 4: Machine learning systems and precision medicine: A conceptual and experimental approach to single individual statistics - p. page_90 14. Chapter 5: Machine learning in digital health, recent trends, and ongoing challenges - p. page_119 15. Chapter 6: Data mining to transform clinical and translational research findings into precision health - p. page_148 16. Section II: Applications of artificial intelligence in precision health - p. page_173 17. Chapter 7: Predictive models in precision medicine - p. page_173 18. Chapter 8: Deep neural networks for phenotype prediction in rare diseases: Inclusion body myositis: A case study - p. page_188 19. Chapter 9: Artificial intelligence for management of patients with intracranial neoplasms - p. page_202 20. Chapter 10: Artificial intelligence to aid the detection of mood disorders - p. page_229 21. Chapter 11: Use of artificial intelligence in Alzheimer’s disease detection - p. page_255 22. Chapter 12: Artificial intelligence to predict atheroma plaque vulnerability - p. page_278 23. Chapter 13: Artificial intelligence in cardiovascular medicine: Applications in the diagnosis of infarction and prognosis of heart failure - p. page_312 24. Chapter 14: Artificial intelligence-based decision support systems for diabetes - p. page_328 25. Chapter 15: Clinical decision support systems to improve the diagnosis and management of respiratory diseases - p. page_357 26. Chapter 16: Artificial intelligence in neuro, head, and neck surgery - p. page_391 27. Chapter 17: Use of artificial intelligence in emergency medicine - p. page_404 28. Chapter 18: Use of artificial intelligence in infectious diseases - p. page_413 29. Chapter 19: Artificial intelligence techniques applied to patient care and monitoring - p. page_438 30. Chapter 20: Use of artificial intelligence in precision nutrition and fitness - p. page_464 31. Section III: Precision systems in practice - p. page_496 32. Chapter 21: Artificial intelligence in precision health: Systems in practice - p. page_496 33. Index - p. page_521
