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Intelligent Precision Healthcare: Multimodal Generative AI for Neurodegenerative Disease Management book cover

1st Edition

Intelligent Precision Healthcare Multimodal Generative AI for Neurodegenerative Disease Management

Edited By Deepika Koundal, Mudassir Khan, Rupali Atul Mahajan, Rajesh Dey Copyright 2027
336 Pages 104 B/W Illustrations
by CRC Press

Artificial Intelligence is reshaping modern healthcare in remarkable ways. This book explores how multimodal generative AI integrates clinical, genetic, and imaging data to improve the understanding and management of neurodegenerative diseases. Bridging technology and medicine, it offers accessible insights into next-generation precision healthcare and its real-world impact. Designed for... Read more
1. General overview of neurodegenerative diseases Major Neuroscience Disorders 2. Generative AI: An Outline Foundation of Generative AI Technologies 3. Healthcare sector whereby Multimodal Data How Do You Use Data from Other data Sources? 4. An AI-Driven Early Diagnosis for Approaches Diagnostic Techniques: Innovations and Smart solutions 5.Therapy Individualization Leveraging AI Insights to Personalize Treatments 6. Neurodegenerative Diseases Case Study Management Proven Deployments and Results 7. The Ethical Dilemma of AI in Healthcare Navigating through Data Privacy and Bias 8. The Future of AI in Study of Neurodegeneration Trends and technologies forthcoming in 9. Interdisciplinary team-working drives innovation. Finding Paths Across Gaps 10. Patient-Centric Approach to AI Patient involvement in artificial intelligence development 11. Legal surroundings of artificial intelligence in healthcare Knowledge of Compliance and Standards 12. Training AI for Medical Professionals Embedding AI Literacy into the heart of Medical Education 13. Using artificial intelligence to revolutionize clinical practise. Effects on workflow and decision-making 14. Organizing data in neurodegenerative studies Problems and answers 15. The economic consequences of artificial intelligence in healthcare Cost effectiveness and value appraise 16. International viewpoints on artificial intelligence in healthcare Dealing with inequalities and chances Interacting patients with tools based on artificial intelligence Improved approaches for engaging with patients New treatment approaches Future directions in care delivery 19. Summary and Invitation to Act Summarizing observations and future directions

Biography

Deepika Koundal is a distinguished academic at the University of Eastern Finland, specializing in Artificial Intelligence, Machine Learning, and healthcare analytics. Her research focuses on intelligent data-driven solutions for medical and biomedical applications, contributing significantly to interdisciplinary innovation and global research collaborations. She has published extensively in reputed international journals and actively leads research initiatives in AI-driven healthcare technologies, fostering academic excellence and industry partnerships worldwide.

 

Mudassir Khan is an accomplished academician and researcher specializing in Big Data Analytics, Deep Learning, AI, and healthcare applications. Holding a Ph.D. in Big Data Analytics using Deep Learning, he is currently pursuing a postdoctoral fellowship at Multimedia University, Malaysia, while serving as Assistant Professor at King Khalid University, Saudi Arabia. With over 14 years of experience, he has authored 100+ SCI/SCOPUS-indexed papers, four books, and edited numerous volumes with leading publishers.

 

Rupali A. Mahajan is an accomplished academician and researcher specializing in Artificial Intelligence, Machine Learning, Deep Learning, and Data Science applications. Holding a Ph.D. in Computer Science and Engineering, she completed her postdoctoral research at the Singapore Institute of Technology. She currently serves as Associate Professor in the Department of Data Science at Vishwakarma Institute of Information Technology, Pune. With over 17 years of professional experience, she has authored 7 books, published 50+ research papers, and held 18 patents across diverse domains.

 

Rajesh Dey is a distinguished researcher specializing in Artificial Intelligence, Machine Learning, and FinTech. Currently a Postdoctoral Fellow at IIUM, Malaysia, he holds a Ph.D. in Adaptive Signal Correction. With over 17 years of experience, he has published extensively and contributed to embedded systems, IoT, robotics, and sustainable EV technologies. He has served in key academic and industry roles, including Associate Professor and Technical Director. A certified Design Thinking Coach, he actively collaborates with international universities and research institutions, mentoring students and driving innovation in emerging technologies.

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