Fundamentals of AI for Medical Education, Research and Practice provides a comprehensive introduction on all aspects of AI application in healthcare, ranging from medical education to diagnostic medicine. The book's chapters are grouped into six sections: an introduction to AI in healthcare, AI in medical education, AI healthcare in research, AI in clinical practice, and future directions and challenges, concluding with practical application of AI tools in health care. Written by an experienced physiologist and medical educationist who is actively involved in all aspects of teaching and…mehr
Fundamentals of AI for Medical Education, Research and Practice provides a comprehensive introduction on all aspects of AI application in healthcare, ranging from medical education to diagnostic medicine. The book's chapters are grouped into six sections: an introduction to AI in healthcare, AI in medical education, AI healthcare in research, AI in clinical practice, and future directions and challenges, concluding with practical application of AI tools in health care. Written by an experienced physiologist and medical educationist who is actively involved in all aspects of teaching and learning, this book will prove to be immense benefit for medical researchers, practicing clinicians, academicians and medical students at all levels.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Dr. Sameer Khan is an esteemed Assistant Professor within the Department of Physiology at the College of Medicine, University of Bisha, in Saudi Arabia. With a distinguished career spanning over 12 years, Dr. Khan has been dedicated to enriching the minds of both undergraduate and postgraduate students through his expertise in human physiology and medical education, where he specializes in interprofessional education with vast experience in both traditional and outcome based curriculum. He has been a part of various college committees, actively involved in curriculum planning, designing, and mapping. Recognized for his academic excellence, Dr. Khan was honored as the most outgoing postgraduate and bestowed with a silver medal for his exceptional performance by the Department of Physiology, KMC Mangalore. Dr. Khan's commitment to advancing medical knowledge extends beyond the classroom; he is the author of the seminal book, "Practical Physiology: A New Approach," a significant contribution to the field, which was published in 2016.
Inhaltsangabe
Part I: Introduction to AI in Healthcare 1. Timeline of Artificial Intelligence (AI) 2. Understanding Artificial Intelligence (AI) in Health care and education 3. Overview of AI Technologies and Their Impact on Healthcare 4. Ethical and Regulatory Considerations in AI Adoption in Healthcare Part II: AI in Medical Education 5. Integration of AI into Medical Curriculum: Challenges and Opportunities 6. AI-enabled Simulation and Virtual Learning Environments 7. AI-based Personalized Learning in Medical Education 8. Assessment with AI in Medical Training Part III: AI in Healthcare Research 9. AI in Clinical Research: Transforming Methodologies and Discoveries 10. Data Science and AI Techniques in Healthcare Research 11. AI-driven Drug Discovery and Development 12. Predictive Analytics and AI in Epidemiological Studies Part IV: AI in Clinical Practice 13. AI in Diagnostics: Enhancing Accuracy and Efficiency 14. AI-enabled Decision Support Systems in Clinical Practice 15. Robotics and AI-assisted Surgery: Advancements and Applications 16. Personalized Medicine and AI-driven Treatment Plans Part V: Future Directions and Challenges 17. AI in Telemedicine and Remote Patient Monitoring 18. Emerging Trends in AI in Healthcare: Innovations and Opportunities 19. Challenges and Limitations of AI Adoption in Healthcare 20. Training the Future Healthcare Workforce for AI Integration Part VI: Case Studies and Practical Applications 21. Case Studies: Real-world Examples of AI Implementation in Healthcare 22. Practical Exercises: Hands-on Activities for Applying AI Concepts in Healthcare
Part I: Introduction to AI in Healthcare 1. Timeline of Artificial Intelligence (AI) 2. Understanding Artificial Intelligence (AI) in Health care and education 3. Overview of AI Technologies and Their Impact on Healthcare 4. Ethical and Regulatory Considerations in AI Adoption in Healthcare Part II: AI in Medical Education 5. Integration of AI into Medical Curriculum: Challenges and Opportunities 6. AI-enabled Simulation and Virtual Learning Environments 7. AI-based Personalized Learning in Medical Education 8. Assessment with AI in Medical Training Part III: AI in Healthcare Research 9. AI in Clinical Research: Transforming Methodologies and Discoveries 10. Data Science and AI Techniques in Healthcare Research 11. AI-driven Drug Discovery and Development 12. Predictive Analytics and AI in Epidemiological Studies Part IV: AI in Clinical Practice 13. AI in Diagnostics: Enhancing Accuracy and Efficiency 14. AI-enabled Decision Support Systems in Clinical Practice 15. Robotics and AI-assisted Surgery: Advancements and Applications 16. Personalized Medicine and AI-driven Treatment Plans Part V: Future Directions and Challenges 17. AI in Telemedicine and Remote Patient Monitoring 18. Emerging Trends in AI in Healthcare: Innovations and Opportunities 19. Challenges and Limitations of AI Adoption in Healthcare 20. Training the Future Healthcare Workforce for AI Integration Part VI: Case Studies and Practical Applications 21. Case Studies: Real-world Examples of AI Implementation in Healthcare 22. Practical Exercises: Hands-on Activities for Applying AI Concepts in Healthcare
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