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Description

This textbook presents artificial intelligence in medicine across eighteen chapters arranged in five parts. Part One builds the conceptual foundations: what artificial intelligence is, how machine learning and deep learning differ, and how medical data is gathered, cleaned, and protected. Part Two surveys medical imaging: radiology, pathology, dermatology, ophthalmology, and point-of-care ultrasound. Part Three moves through clinical specialties, with chapters on cardiology, oncology, neurology and psychiatry, and critical care. Part Four addresses natural language processing, clinical decision support systems, and drug discovery. Part Five turns to hospital implementation, ethics and algorithmic bias, regulation and legal liability, the clinician's working relationship with these tools, and future directions. Every chapter follows the same fixed structure. It opens with a list of learning objectives, works through five or six numbered sections of narrative exposition, and closes with a key points summary, an extended clinical case, and its own reference list. Callout boxes marked Clinical Pearl, Pitfall, Protocol, and Key Point interrupt the narrative where a practical caution or a step-by-step framework belongs. The text explains how these systems work through clinical analogy rather than mathematics. It contains no equations and no programming code. A reader who has never trained a model should still be able to follow why an algorithm generalizes poorly to a different hospital, or why a confident output can nonetheless be wrong. Each chapter carries a comparison table setting out the evidence and the deployment status behind the tools that chapter describes, and annotated figures illustrate model architectures, clinical workflows, and representative imaging findings. A glossary of roughly one hundred terms and a back-matter index support use as a reference rather than a single read-through. The book is intended for medical students, residents and fellows, practising clinicians, and hospital administrators evaluating these tools. Note Readers should confirm all clinical values, regulatory positions, and product information against current guidelines and manufacturer documentation before applying them in practice. This book is not affiliated with, sponsored by, or endorsed by any medical society, regulatory agency, or certifying board. The frontispiece in the front matter is an AI-generated illustration.

Product Specifications

Format: paperback
ASIN: B0HLXLRSVQ
Category: Books > Subjects > Health, Family & Lifestyle > Medical & Healthcare Practitioners > Other Branches of Medicine > Medical Imaging
Domain: Amazon UK
Release Date: 04 October 2026
Listed Since: 04 October 2026

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Textbook Of Artificial Intelligence In Medicine: Clinical Applications, Implementation, and Ethics for Physicians and Medical Students

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Textbook Of Artificial Intelligence In Medicine: Clinical Applications, Implementation, and Ethics for Physicians and Medical Students

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