Description

AI for Healthcare provides a comprehensive, evidence-based guide to how artificial intelligence is transforming medicine. Structured in three parts, the book first demystifies core technologies (machine learning, deep learning, large language models, and AI agents) through concrete clinical examples.

It then examines real-world applications already deployed in hospitals worldwide, including diagnostic imaging, predictive medicine, connected health, digital mental health therapies, AI-powered disability assistance, and hospital operations optimization.

The final part addresses the conditions for responsible implementation, including ethics, trust-building, cybersecurity, and regulatory frameworks. Each chapter is enriched with exclusive interviews featuring physician-researchers and technology leaders from institutions such as Stanford, Harvard, and MIT, as well as operational case studies from innovative technology companies and clinics.

The book bridges the gap between technical possibility and clinical reality. It is written for healthcare professionals, hospital decision-makers, health technology leaders, researchers, and policymakers who need to understand, evaluate, and act on AI within their organizations. Readers will gain a clear, jargon-free understanding of what AI can and cannot do today, the critical questions to ask before any deployment, and a practical framework for successfully implementing AI while keeping patients at the center.