ARTIFICIAL INTELLIGENCE IN CLINICAL MEDICINE: Principles, Clinical Applications, Decision Support, Safety, Ethics, Governance, and Human-Centered Healthcare - Softcover

Inhaltsangabe

ARTIFICIAL INTELLIGENCE IN CLINICAL MEDICINE 2026–2027
Principles, Clinical Applications, Decision Support, Safety, Ethics, Governance, and Human-Centered Healthcare

DISCOVER HOW ARTIFICIAL INTELLIGENCE IS TRANSFORMING MODERN MEDICINE—AND LEARN HOW TO UNDERSTAND, EVALUATE, AND APPLY IT RESPONSIBLY IN CLINICAL PRACTICE!

Artificial intelligence is reshaping healthcare, from medical diagnosis and predictive analytics to clinical decision support, medical imaging, patient monitoring, and personalized treatment. But as AI becomes increasingly integrated into medicine, one critical question remains: How can healthcare professionals harness its potential while protecting patient safety and maintaining sound clinical judgment?
Artificial Intelligence in Clinical Medicine 2026–2027 provides a comprehensive, practical, and accessible guide to understanding AI in modern healthcare.
Designed for medical students, nursing students, physicians, advanced practice providers, allied health professionals, and healthcare educators, this textbook bridges the gap between complex AI technologies and real-world clinical practice.
Rather than focusing solely on technical algorithms, it explains how AI systems work, where they can support healthcare decisions, how to recognize their limitations, and why human expertise remains essential.
WHAT YOU'LL DISCOVER INSIDE

• AI and Machine Learning Fundamentals: Understand artificial intelligence, machine learning, deep learning, clinical data, model development, and performance evaluation.
• Clinical Decision Support: Explore how AI assists diagnostic reasoning, risk assessment, clinical predictions, and evidence-informed decisions.
• Generative AI in Healthcare: Understand large language models, natural language processing, clinical documentation, automated summaries, and the risks of inaccurate AI-generated information.
• Medical Imaging and Diagnostics: Discover AI applications in radiology, digital pathology, ECG interpretation, and diagnostic image analysis.
• AI Across Medical Specialties: Examine applications in emergency medicine, cardiology, neurology, oncology, internal medicine, and chronic disease management.
• Predictive Analytics and Patient Monitoring: Learn how AI supports early warning systems, deterioration detection, remote monitoring, and risk stratification.
• Patient Safety and Ethical AI: Understand algorithmic bias, privacy, fairness, clinical reliability, human oversight, and professional accountability.
• Healthcare AI Implementation: Explore validation, workflow integration, governance, regulatory considerations, and institutional oversight.
• Emerging AI Technologies...

MORE THAN JUST A TEXTBOOK
This comprehensive educational resource features 25 structured chapters, clinical scenarios, practical exercises, multiple-choice questions, explanatory answers, medical illustrations, reference tables, professional checklists, focused appendices, and a glossary to strengthen understanding and support continued learning.
WHO SHOULD READ THIS BOOK?
Medical and nursing students, Physicians and clinical trainees, Nurse practitioners and advanced practice providers, Allied health and public health professionals, Healthcare educators and administrators, Health informatics and digital health learners, Healthcare professionals seeking practical AI literacy
PREPARE FOR THE FUTURE OF HEALTHCARE
You don't need to be a programmer or data scientist to understand artificial intelligence in medicine.
Whether you're beginning your healthcare education, expanding your professional knowledge, or exploring how AI can support safer and more effective clinical care, this book provides the essential framework for navigating an increasingly AI-enabled healthcare environment.

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