This book provides an in-depth exploration of AI safety in healthcare. It bridges the gap between technical innovation and patient protection. It examines emerging methodologies for risk management, transparency, and robust AI system design used specifically in medical applications.
Readers will gain insights into the ethical considerations that surround AI deployment, techniques for improving the explainability and accountability of AI models, and the implementation of safety protocols to detect and prevent AI failures. The book also discusses the evolving regulatory view that shapes AI adoption and how privacy-preserving technologies can enable safer data sharing across institutions. In highlighting both current challenges and future directions, the book makes a meaningful contribution to the safe, responsible, and trustworthy integration of AI in healthcare systems.
This is an illuminating read for researchers, practitioners, policymakers, and healthcare providers interested in acquiring the knowledge needed to harness AI’s potential while safeguarding human health and well-being.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Azadeh Zamanifar, Head of AI/IT Department, Science and research branch, Islamic Azad University, Tehran, Iran.
Amir Taherkordi, Professor of Computer Science, University of Oslo, Norway.
Amirfarhad Farhadi, Postdoctoral Fellow, Iran University of Science and Technology, Tehran, Iran.
The book explores real-world applications of explainable AI (XAI) safely in healthcare, focusing on disease diagnosis, treatment planning, and patient management, while demonstrating how XAI enhances clinical decision-making and patient outcomes.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Hardcover. Etat : new. Hardcover. This book provides an in-depth exploration of AI safety in healthcare. It bridges the gap between technical innovation and patient protection. It examines emerging methodologies for risk management, transparency, and robust AI system design used specifically in medical applications.Readers will gain insights into the ethical considerations that surround AI deployment, techniques for improving the explainability and accountability of AI models, and the implementation of safety protocols to detect and prevent AI failures. The book also discusses the evolving regulatory view that shapes AI adoption and how privacy-preserving technologies can enable safer data sharing across institutions. In highlighting both current challenges and future directions, the book makes a meaningful contribution to the safe, responsible, and trustworthy integration of AI in healthcare systems. This is an illuminating read for researchers, practitioners, policymakers, and healthcare providers interested in acquiring the knowledge needed to harness AIs potential while safeguarding human health and well-being. The book explores real-world applications of explainable AI (XAI) safely in healthcare, focusing on disease diagnosis, treatment planning, and patient management, while demonstrating how XAI enhances clinical decision-making and patient outcomes. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781041249610
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Hardcover. Etat : new. Hardcover. This book provides an in-depth exploration of AI safety in healthcare. It bridges the gap between technical innovation and patient protection. It examines emerging methodologies for risk management, transparency, and robust AI system design used specifically in medical applications.Readers will gain insights into the ethical considerations that surround AI deployment, techniques for improving the explainability and accountability of AI models, and the implementation of safety protocols to detect and prevent AI failures. The book also discusses the evolving regulatory view that shapes AI adoption and how privacy-preserving technologies can enable safer data sharing across institutions. In highlighting both current challenges and future directions, the book makes a meaningful contribution to the safe, responsible, and trustworthy integration of AI in healthcare systems. This is an illuminating read for researchers, practitioners, policymakers, and healthcare providers interested in acquiring the knowledge needed to harness AIs potential while safeguarding human health and well-being. The book explores real-world applications of explainable AI (XAI) safely in healthcare, focusing on disease diagnosis, treatment planning, and patient management, while demonstrating how XAI enhances clinical decision-making and patient outcomes. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9781041249610
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Azadeh Zamanifar, Head of AI/IT Department, Science and research branch, Islamic Azad University, Tehran, Iran. Amir Taherkordi, Professor of Computer Science, University of Oslo, Norway. Amirfarhad Farhadi, Postdoctoral Fellow, Iran Univer. N° de réf. du vendeur 2875271630
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