COMPREHENSIVE ARTIFICIAL INTELLIGENCE IN MEDICINE: From Algorithmic Foundations to Bedside Application — An Evidence-Based Resource for Medical Students and Clinicians.

Artificial intelligence is entering clinical practice fast. This textbook helps you understand it with confidence, caution, and professional judgment. Comprehensive Artificial Intelligence in Medicine is a clinically grounded resource for readers who need more than hype and more than coding theory. It explains how AI, machine learning, deep learning, medical data, model validation, decision support, imaging tools, genomics, drug discovery, EHR documentation, ethics, regulation, and implementation connect to real healthcare practice. Written for medical students, residents, clinicians, educators, health system leaders, pharmacists, nurses, and allied health professionals, this guide turns complex technical ideas into clear clinical understanding. Instead of treating AI as a mystery, it shows how algorithms are developed, evaluated, governed, and responsibly integrated into patient-centered care. Inside, you will learn to: - Understand the core language of AI, machine learning, deep learning, NLP, computer vision, and clinical prediction- Evaluate AI tools using sensitivity, specificity, AUC, calibration, validation, bias, and real-world performance- Connect AI applications to radiology, pathology, surgery, oncology, pharmacology, genomics, critical care, public health, and education- Recognize ethical, legal, privacy, safety, and equity issues before adopting clinical AI systems- Apply structured worksheets and case-based thinking to strengthen AI literacy across healthcare settings- Build practical awareness of hospital implementation, governance, workflow integration, and post-deployment monitoring This book is not a programming manual or a substitute for professional clinical guidance. It is a practical educational foundation for understanding how AI is reshaping modern healthcare. Use it to strengthen your clinical AI literacy, evaluate emerging tools more carefully, and participate responsibly in the future of technology-enabled patient care.

Pagina's: 443, Paperback, Independently published