Multimodal AI in Healthcare
Description
This book is a unique guide that explores how multimodal AI is revolutionizing various domains of healthcare. It thoroughly discusses different data modalities-ranging from medical images and genomics to patient records-and techniques to combine diverse sources to create richer, more accurate insights.
The book delves into the transformative role of Multimodal Artificial Intelligence (AI) in healthcare, covering diagnosis, treatment, and rehabilitation. It highlights advanced AI-driven diagnostic techniques, such as early cancer detection, AI in TB diagnostics, and precision diagnostics in clinical microbiology, showcasing AI's ability to enhance disease identification. Additionally, it examines AI's impact on critical and emergency care, with chapters on multimodal integration in stroke treatment, AI-driven systems in ICUs, pediatric emergency care, and AI applications in surgery and surgical healthcare.
A key focus is AI in primary and public healthcare, addressing its role in strengthening primary health systems, promoting health equity, and revolutionizing oral healthcare. The book also discusses the use of multimodal AI chatbots for medical laboratory result interpretation and AI's role in medical laboratory science and practice, emphasizing its potential to streamline diagnostic workflows.
Beyond traditional healthcare, the book explores AI's application in mental health and stress management, with insights into multimodal AI in suicide risk prediction and AI-driven music therapy for stress management. It also examines how AI is transforming surgery by enhancing precision, improving outcomes, and streamlining workflows, while emphasizing the irreplaceable role of human intuition, empathy, and patient-centered care.
This comprehensive guide not only illustrates how multimodal AI is transforming medical diagnostics and treatments but also paves the way for a future where precision health becomes the standard. It serves as an invaluable resource for students, scholars, and experts in the field, guiding healthcare professionals, researchers, and policymakers in leveraging multimodal AI to improve outcomes, reduce disparities, and create a smarter, patient-centric healthcare ecosystem.
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Persons
Dr. Jeetendra Kumar holds a Ph.D. in Computer Science from GLA University, Mathura. He has been an Assistant Professor in the Department of Computer Science and Application at Atal Bihari Vajpayee University, Bilaspur, Chhattisgarh, India, for the past 13 years. With an M.Sc. and M.Tech. in Computer Science, he has published numerous research articles on topics like sentiment analysis, fall detection using machine learning, IoT applications, and automatic question generation. Dr. Kumar has contributed book chapters on neuroscience, smartphone applications, and fog computing in healthcare, and edited a book with CRC Press, Taylor and Francis. He has completed two research projects sponsored by the State Planning Commission, C.G., and Commonwealth Media Centre for Asia (CEMCA), New Delhi. He is a member of prestigious academic societies such as IEEE, the Indian Science Congress, IAENG, ICSES, and IAASSE.
Dr. U Venkatesh , MBBS, MD (Community Medicine), is a renowned public health researcher, educator, and author with extensive experience in health policy, epidemiology, and data-driven decision-making. He is an Assistant Professor at AIIMS Gorakhpur and the National Coordinator of the National Centre for Policy Research in Tobacco Control (NCPRTC) and the Centre for Policy Research & Data Analytics in Health and Environment (CePRAHE). Dr. Venkatesh has led multiple ICMR-funded and internationally funded research projects, securing over ?10 crores in research grants. His work has been published in top-tier journals like The Lancet Regional Health - Southeast Asia, Frontiers in Public Health, and Cambridge Prisms: Global Mental Health. He has authored four books, including "Untold Stories of Tobacco (Youth Voices)" and "PSM Residency Made Easy." As a National Trainer for Ayushman Bharat, he has contributed to capacity-building initiatives and the development of government policy documents and training manuals for healthcare professionals. He is also a peer reviewer for reputed medical and public health journals, influencing evidence-based policymaking in areas such as tobacco control, climate change, and health system strengthening.
Content
The Rise of Multimodal AI in Healthcare - A New Frontier.- Demography and Population Intelligence in Multimodal AI for Healthcare.- Geospatial Intelligence and GIS in Multimodal AI for Healthcare.- Artificial Intelligence for Health Equity: Bridging Gaps with Multimodal Intelligence.- Role of AI in TB Diagnostics in India.- Role of Artificial Intelligence in Cancer.- Intelligent Diagnosis: Leveraging Artificial Intelligence to Detect and Manage Infectious and Non-Infectious Diseases.- Revolutionizing Oral Healthcare: Artificial Intelligence as a Paradigm Shift in Public Health Dentistry.- Fusion Intelligence for Anemia Diagnosis: Multimodal AI Approaches for Early Detection and Integrated Management.- Legal and ethical dimensions of AI-driven multimodal treatment response systems in the Intensive Care Units.- Multimodal Artificial Intelligence in Pediatric Emergency and Critical Care.- Multimodal AI and Telemedicine in Remote Health Monitoring.- Current Implications and Future Directions of Artificial Intelligence in Surgery and Related Fields.- Fusion of Artificial Intelligence in Surgical Healthcare.- Artificial Intelligence in Primary Healthcare.- Role of Artificial Intelligence in strengthening the primary health care system.- Multimodal AI in Suicide Risk Prediction: Behavioural, Physiological, and Digital Biomarkers.