AI in Medicine: From Machine Learning Foundations to Evidence-Based Clinical Applications, (Paperback)

<p><b>AI in Medicine</b> is for readers who want to understand how artificial intelligence is actually changing clinical care, not just hear broad claims about the future. AI is already influencing <b>diagnosis, imaging, risk prediction, clinical decision support, and workflow across healthcare</b>, and clinicians increasingly need enough understanding to judge where it helps, where it falls short, and how to use it responsibly.</p><p>This book starts where many readers are: curious, aware that AI matters, but frustrated by explanations that are either too technical or too vague. Instead of treating machine learning like a purely engineering topic, <b>AI in Medicine</b> explains the foundations in a way that stays connected to patient care. It helps readers understand the core ideas behind modern AI systems, how they are evaluated, and why some tools improve clinical decisions while others require caution. That makes the subject easier to grasp and far more useful in practice.</p><p>What gives this book real value is its focus on evidence-based clinical application. Readers are guided through how AI is being used in imaging, prediction, decision support, and data-driven care, while also learning the limits of these systems, including bias, overreliance, and the continuing need for sound human judgment. In other words, this is not a book about hype. It is a book about understanding what AI can do, what it cannot do, and how informed clinicians can engage with it intelligently.</p><p>Whether you are a student trying to understand the field, a clinician wanting to stay current, or a healthcare professional looking for a clearer framework for AI-driven medicine, <b>AI in Medicine</b> offers a practical path through one of the most important changes in modern healthcare.</p><p><b>Inside this book, readers will gain: </b></p><ol><li>a clear understanding of machine learning foundations relevant to medicine</li><li>practical insight into AI in diagnosis, imaging, and decision support</li><li>a stronger grasp of evidence-based clinical applications</li><li>a realistic view of both the promise and limits of AI in healthcare</li><li>a more confident understanding of how technology and clinical judgment work together</li></ol><p><br><b>Add <i>AI in Medicine</i> to your library if you want a guide that makes artificial intelligence clearer, more clinically useful, and far easier to understand in the real world.</b></p>

• AI in Medicine: From Machine Learning Foundations to Evidence-Based Clinical Applications, (Paperback)
• Author: Independently Published
• ISBN: 9798258887665
• Format: Paperback
• Publication Date: 2026-04-26
• Page Count: 182