Intelligent Precision Healthcare
Description
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 researchers, clinicians, and informed readers alike, it highlights practical applications, ethical considerations, and future possibilities in AI-driven neurological care.
This volume provides a comprehensive examination of how multimodal generative AI techniques can be applied to the diagnosis, monitoring, and management of neurodegenerative disorders such as Alzheimer's disease and Parkinson's disease. It covers foundational concepts in precision healthcare, multimodal data integration (including genetic, clinical, and neuroimaging data), and advanced modeling approaches for disease progression prediction. The book also explores synthetic data generation for rare conditions, explainable and interpretable AI models for clinical decision support, and AI-driven early detection systems. Dedicated chapters address ethical, legal, and regulatory considerations, interdisciplinary collaboration, and patient-centric AI design. Through case studies and real-world applications, the book demonstrates how intelligent systems can enhance personalized treatment planning, improve clinical outcomes, and support data-driven healthcare innovation.
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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.
Content
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