Full Description
This book provides a platform for research on deep generative models, with an emphasis on its healthcare applications. The book addresses the unanswered questions that stop these approaches from making a huge difference in real-world clinical practice. The goal of this book is to bring together a wide range of methodologies which are using generative models in health care-related contexts. The book leverages the recent methodological advancements in deep generative models to address critical health-care challenges across all data-types, paving the way for their practical integration into the healthcare system and elevate their impact on the future of healthcare.
Contents
Preface. 1. Introduction To Deep Generative Models. 2. A Deep Dive into Generative Model Types beyond Imagination. 3. A New Wave of Generative Flow Networks in Streaming Healthcare with Artificial Intelligence. 4. Diffusion Models for Medical Applications. 5. Modeling Disease Progression with Generative Time Series Models: A New Approach to Complex Disease Trajectories. 6. Advancing Synthetic EEG Signal Generation for Biomedical Research: A Diffusion Model Approach. 7. Leveraging Semi-Supervised Diffusion Models for Accurate Brain Age Prediction. 8. The Precision Edge of Deep Generative Models for Enhanced Differential Diagnosis. 9. AI-Driven Implantable Medical Devices Using Deep Generative Models. 10. Deep Generative AI-Based Multimodal Biometric Authentication System for enhanced Security and Accessibility in Healthcare Applications. 11. Deep Generative Models for Alzheimer's Disease Diagnosis. 12. Regulating Deep Generative Models: Ethical and Legal Considerations for Healthcare AI. 13. Research Challenges in Deep Generative Models for Healthcare and Medical Applications.
