This volume brings together cutting-edge research at the intersection of artificial intelligence, clinical care, and public health. While it highlights the impact of generative AI, including large language models, it also delves into broader challenges such as fairness, robustness, scalability, and explainability. 

Chapters explore: 

Rather than focusing on isolated use cases or technical performance alone, this book offers a systems-level perspective, bridging computational innovation with clinical and ethical relevance. 

Designed for researchers, healthcare professionals, and innovators, this collection provides critical insights for anyone aiming to responsibly develop or implement AI in health contexts.