Overview

Clinical decision making sits at the heart of healthcare, where complexity, uncertainty, and time pressure intersect with the responsibility for human life. AI and Generative AI for Clinical Decision Making is written to help clinicians, data scientists, healthcare leaders, and students understand how modern artificial intelligence, particularly generative models are reshaping the way clinical insights are created, interpreted, and applied. From foundational concepts to advanced applications, this book bridges medicine and technology, explaining not only how AI systems work, but how they can be responsibly integrated into real-world clinical environments to enhance accuracy, consistency, and patient-centered care. The chapters progress from core principles and data foundations to high-impact use cases such as diagnosis, risk prediction, treatment planning, and personalized medicine, while also addressing workflow integration, safety, ethics, and regulatory realities. Looking ahead, the book explores the evolving role of AI as a clinical partner rather than a replacement for human judgment. The capstone, research, and industry projects are designed to translate theory into practice, enabling readers to critically evaluate AI solutions, design clinically meaningful applications, and contribute to the future of evidence-based, AI-augmented healthcare.

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