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ARTIFICIAL INTELLIGENCE IN HEALTHCARE MEDICINE: Understanding clinical applications, decision support, patient safety, privacy, responsible implementation, and emerging medical technologies - Softcover

Whitcombe, Arden R.

 
9798176112382: ARTIFICIAL INTELLIGENCE IN HEALTHCARE MEDICINE: Understanding clinical applications, decision support, patient safety, privacy, responsible implementation, and emerging medical technologies

Inhaltsangabe

ARTIFICIAL INTELLIGENCE IN HEALTHCARE MEDICINE

Artificial intelligence is changing how medicine is practiced, how clinical information is interpreted, and how healthcare decisions are supported. But understanding AI in medicine requires more than knowing what machine learning or generative AI can do. Clinicians and healthcare professionals need to understand where these technologies can genuinely add value, where their limitations matter, and how to use them responsibly in real clinical environments.

Artificial Intelligence in Healthcare Medicine was created to make this rapidly evolving field easier to understand and more useful for medical practice. Instead of treating AI as a purely technical subject, this book connects artificial intelligence with the practical problems healthcare professionals face every day, from clinical decision-making and diagnosis to risk prediction, patient monitoring, medical imaging, treatment planning, workflow improvement, and personalized care.

Inside, readers will explore:

  • How artificial intelligence, machine learning, deep learning, and generative AI are being applied in medicine

  • How AI can support clinical reasoning, diagnosis, risk assessment, and treatment decisions

  • The role of AI in medical imaging, electronic health records, precision medicine, and patient monitoring

  • Clinical decision-support systems and how they can complement healthcare professionals

  • How predictive models can assist with early detection and risk stratification

  • The opportunities and limitations of generative AI and large language models in healthcare

  • Data quality, privacy, bias, transparency, explainability, and patient safety

  • How to evaluate AI tools before trusting their recommendations

  • Implementation challenges when AI moves from research environments into real clinical workflows

  • Ethical, professional, regulatory, and human-centered considerations surrounding medical AI

  • Emerging developments that are shaping the future of AI-assisted healthcare

The real value of this book is practical understanding.

AI can produce impressive results in selected medical tasks, but strong technical performance does not automatically mean that an AI system will improve patient care in every real-world setting. Recent evidence continues to show the importance of external validation, workflow integration, fairness, transparency, and careful clinical oversight.

This book therefore takes a balanced approach. It explores what AI can do while also addressing what it cannot reliably do, helping readers develop a more informed approach to AI-assisted medicine rather than blindly accepting or rejecting the technology.

Updated for 2026 and beyond, this book is designed for medical students, physicians, residents, nurses, allied health professionals, healthcare researchers, clinical educators, health administrators, and anyone who wants to understand the growing intersection of artificial intelligence and modern healthcare.

Whether you are beginning to explore medical AI or already encountering AI-powered tools in clinical practice, this book provides a practical foundation for understanding the technology, evaluating its usefulness, recognizing its risks, and making better-informed decisions about its role in patient care.

If you want to understand not just what artificial intelligence can do in medicine, but how to think about its real clinical value, this book provides a practical place to start.

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