The Law for AI in Healthcare

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Bol This book presents a timely overview of how artificial intelligence (AI) is transforming modern healthcare. Combining legal, ethical and practical viewpoints, it explores the impact of AI on patients, clinicians, healthcare organisations and regulators in the EU, UK and US. This book presents a timely overview of how artificial intelligence (AI) is transforming modern healthcare. Combining legal, ethical and practical viewpoints, it explores the impact of AI on patients, clinicians, healthcare organisations and regulators in the EU, UK and US. It delves into the fundamentals of clinical AI systems, explaining how they function and make decisions. It also addresses practical concerns such as safety, fairness, transparency and patient trust. Drawing on real-world examples, such as AI-assisted diagnosis, clinical decision-support tools and machine-learning programmes in hospitals, this book highlights the challenges of aligning law and policy with rapid technological advancements. Key topics explored include bias in medical algorithms, accountability for automation errors and the importance of patient autonomy and data rights for digitally enabled care. The book will appeal to students, policymakers, practitioners and anyone looking to understand the future law of AI in healthcare.

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This book presents a timely overview of how artificial intelligence (AI) is transforming modern healthcare. Combining legal, ethical and practical viewpoints, it explores the impact of AI on patients, clinicians, healthcare organisations and regulators in the EU, UK and US. This book presents a timely overview of how artificial intelligence (AI) is transforming modern healthcare. Combining legal, ethical and practical viewpoints, it explores the impact of AI on patients, clinicians, healthcare organisations and regulators in the EU, UK and US. It delves into the fundamentals of clinical AI systems, explaining how they function and make decisions. It also addresses practical concerns such as safety, fairness, transparency and patient trust. Drawing on real-world examples, such as AI-assisted diagnosis, clinical decision-support tools and machine-learning programmes in hospitals, this book highlights the challenges of aligning law and policy with rapid technological advancements. Key topics explored include bias in medical algorithms, accountability for automation errors and the importance of patient autonomy and data rights for digitally enabled care. The book will appeal to students, policymakers, practitioners and anyone looking to understand the future law of AI in healthcare.


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Merk Taylor & Francis Group Limited
EAN
  • 9781041140665
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