Advancing Integrative Medicine Through Medical Intelligence: Introduction to Medical Intelligence with Integrative Medicine" explores the synergy between advanced technologies like AI and data analytics, and traditional medicine. This comprehensive book examines how these fields converge to enhance healthcare outcomes.
The book covers key topics such as the role of AI in modern medicine, integration of traditional practices like Ayurveda and Unani with AI, and holistic approaches for patient care. It also includes AI-assisted mental health interventions, disease prevention through traditional methods, and AI in diagnosing chronic diseases and managing pain.
Academics, researchers, and healthcare professionals will find this book invaluable for understanding how to combine AI and integrative medicine to improve health outcomes. It offers practical case studies and explores emerging trends that will shape the future of healthcare, making it a crucial resource for those interested in the evolving landscape of medical practices.
1. Cover image - p. c 2. Title page - p. iii 3. Copyright - p. iv 4. Contents - p. v 5. Contributors - p. xxi 6. About the Editors - p. xxvii 7. Chapter 1 Multidisciplinary approach for female sexual dysfunction: Bridging Unani and contemporary medicine along with artificial intelligence innovations - p. 1 8. Chapter 2 Current advancements of AI-driven modern medicine - p. 31 9. Chapter 3 Deep learning for clinical research: Current issues and future recommendations - p. 65 10. Chapter 4 Integrating artificial intelligence into holistic nursing: Enhancing compassionate and personalized care - p. 81 11. Chapter 5 Human metapneumovirus: Worldwide research and therapeutic strategies - p. 101 12. Chapter 6 Modern approaches to craniofacial anomalies: The role of artificial intelligence and integrative therapies - p. 131 13. Chapter 7 Utilizing large language models for early disease identification - p. 153 14. Chapter 8 Molecular docking and network pharmacology insights of Sesamum indicum Linn in pelvic inflammatory disease - p. 167 15. Chapter 9 Artificial intelligence-driven strategies in the identification and treatment of ischemic heart disease - p. 191 16. Chapter 10 Automated grading of diabetic retinopathy using retina insighter and convolutional neural networks - p. 207 17. Chapter 11 Integrative perspectives on Lawsonia inermis L.: From ethnomedicine and pharmacology to clinical utility and artificial intelligence–driven discoveries - p. 227 18. Chapter 12 Role of integrative medicine in disease prevention in women's health: Role for artificial intelligence and machine learning - p. 257 19. Chapter 13 Artificial intelligence in cancer medicine: Nanotherapeutics and integrative approaches - p. 289 20. Chapter 14 Role of artificial intelligence in enhancing the development, validation, and application of Unani formulations for the management of COVID-19 - p. 303 21. Chapter 15 Integrating AI into traditional Indian medicine: Personalization, validation, and global scale - p. 321 22. Chapter 16 Traditional Chinese medicine with artificial intelligence: Challenges and future prospects - p. 349 23. Chapter 17 Recent advances in integrative medicine: Current challenges and future recommendations - p. 371 24. Chapter 18 Artificial intelligence in predictive toxicology: A new paradigm for safety profiling of Unani drugs - p. 407 25. Index - p. 421
Advancing Integrative Medicine Through Medical Intelligence: Introduction to Medical Intelligence with Integrative Medicine" explores the synergy between advanced technologies like AI and data analytics, and traditional medicine. This comprehensive book examines how these fields converge to enhance healthcare outcomes.
The book covers key topics such as the role of AI in modern medicine, integration of traditional practices like Ayurveda and Unani with AI, and holistic approaches for patient care. It also includes AI-assisted mental health interventions, disease prevention through traditional methods, and AI in diagnosing chronic diseases and managing pain.
Academics, researchers, and healthcare professionals will find this book invaluable for understanding how to combine AI and integrative medicine to improve health outcomes. It offers practical case studies and explores emerging trends that will shape the future of healthcare, making it a crucial resource for those interested in the evolving landscape of medical practices.
1. Cover image - p. c 2. Title page - p. iii 3. Copyright - p. iv 4. Contents - p. v 5. Contributors - p. xxi 6. About the Editors - p. xxvii 7. Chapter 1 Multidisciplinary approach for female sexual dysfunction: Bridging Unani and contemporary medicine along with artificial intelligence innovations - p. 1 8. Chapter 2 Current advancements of AI-driven modern medicine - p. 31 9. Chapter 3 Deep learning for clinical research: Current issues and future recommendations - p. 65 10. Chapter 4 Integrating artificial intelligence into holistic nursing: Enhancing compassionate and personalized care - p. 81 11. Chapter 5 Human metapneumovirus: Worldwide research and therapeutic strategies - p. 101 12. Chapter 6 Modern approaches to craniofacial anomalies: The role of artificial intelligence and integrative therapies - p. 131 13. Chapter 7 Utilizing large language models for early disease identification - p. 153 14. Chapter 8 Molecular docking and network pharmacology insights of Sesamum indicum Linn in pelvic inflammatory disease - p. 167 15. Chapter 9 Artificial intelligence-driven strategies in the identification and treatment of ischemic heart disease - p. 191 16. Chapter 10 Automated grading of diabetic retinopathy using retina insighter and convolutional neural networks - p. 207 17. Chapter 11 Integrative perspectives on Lawsonia inermis L.: From ethnomedicine and pharmacology to clinical utility and artificial intelligence–driven discoveries - p. 227 18. Chapter 12 Role of integrative medicine in disease prevention in women's health: Role for artificial intelligence and machine learning - p. 257 19. Chapter 13 Artificial intelligence in cancer medicine: Nanotherapeutics and integrative approaches - p. 289 20. Chapter 14 Role of artificial intelligence in enhancing the development, validation, and application of Unani formulations for the management of COVID-19 - p. 303 21. Chapter 15 Integrating AI into traditional Indian medicine: Personalization, validation, and global scale - p. 321 22. Chapter 16 Traditional Chinese medicine with artificial intelligence: Challenges and future prospects - p. 349 23. Chapter 17 Recent advances in integrative medicine: Current challenges and future recommendations - p. 371 24. Chapter 18 Artificial intelligence in predictive toxicology: A new paradigm for safety profiling of Unani drugs - p. 407 25. Index - p. 421
