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AI in Healthcare Implementation: A Practical Guide to Deploying Clinical Artificial Intelligence for Safe, Scalable, and Compliant Patient Care - Couverture souple
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Synopsis
Artificial Intelligence (AI) in healthcare is transforming diagnostics, patient care, and hospital operations—but most AI projects fail at the implementation stage.
AI in Healthcare Implementation is a practical, real-world guide to deploying clinical AI systems safely, effectively, and at scale. Designed for clinicians, healthcare leaders, and AI professionals, this book bridges the critical gap between building AI models and making them work in real clinical environments.
Inside this book, you will learn how to:
Design and execute end-to-end AI deployment strategies in healthcare
Integrate AI systems with EHR/EMR using standards like HL7 and FHIR
Navigate global regulatory frameworks including FDA, EU AI Act, and DPDP
Validate AI systems for real-world clinical performance and patient safety
Identify and prevent common AI failures such as bias, drift, and workflow misalignment
Build governance, monitoring, and compliance systems for long-term success
This book focuses not on theory, but on real implementation—covering data readiness, infrastructure, clinical workflows, risk management, and continuous monitoring.
With global case studies, practical frameworks, and step-by-step guidance, this is an essential resource for anyone involved in digital health, clinical AI, and healthcare innovation.
Whether you are a doctor, data scientist, hospital administrator, policymaker, or health-tech entrepreneur, this book provides the tools to move from AI experimentation to safe, scalable, and impactful deployment in healthcare systems worldwide.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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AI in Healthcare Implementation (Paperback)
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Paperback. Etat : new. Paperback. Artificial Intelligence (AI) in healthcare is transforming diagnostics, patient care, and hospital operations-but most AI projects fail at the implementation stage.AI in Healthcare Implementation is a practical, real-world guide to deploying clinical AI systems safely, effectively, and at scale. Designed for clinicians, healthcare leaders, and AI professionals, this book bridges the critical gap between building AI models and making them work in real clinical environments.Inside this book, you will learn how to: Design and execute end-to-end AI deployment strategies in healthcareIntegrate AI systems with EHR/EMR using standards like HL7 and FHIRNavigate global regulatory frameworks including FDA, EU AI Act, and DPDPValidate AI systems for real-world clinical performance and patient safetyIdentify and prevent common AI failures such as bias, drift, and workflow misalignmentBuild governance, monitoring, and compliance systems for long-term successThis book focuses not on theory, but on real implementation-covering data readiness, infrastructure, clinical workflows, risk management, and continuous monitoring.With global case studies, practical frameworks, and step-by-step guidance, this is an essential resource for anyone involved in digital health, clinical AI, and healthcare innovation.Whether you are a doctor, data scientist, hospital administrator, policymaker, or health-tech entrepreneur, this book provides the tools to move from AI experimentation to safe, scalable, and impactful deployment in healthcare systems worldwide. 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 9798253272503
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AI in Healthcare Implementation: A Practical Guide to Deploying Clinical Artificial Intelligence for Safe, Scalable, and Compliant Patient Care
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AI in Healthcare Implementation (Paperback)
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Paperback. Etat : new. Paperback. Artificial Intelligence (AI) in healthcare is transforming diagnostics, patient care, and hospital operations-but most AI projects fail at the implementation stage.AI in Healthcare Implementation is a practical, real-world guide to deploying clinical AI systems safely, effectively, and at scale. Designed for clinicians, healthcare leaders, and AI professionals, this book bridges the critical gap between building AI models and making them work in real clinical environments.Inside this book, you will learn how to: Design and execute end-to-end AI deployment strategies in healthcareIntegrate AI systems with EHR/EMR using standards like HL7 and FHIRNavigate global regulatory frameworks including FDA, EU AI Act, and DPDPValidate AI systems for real-world clinical performance and patient safetyIdentify and prevent common AI failures such as bias, drift, and workflow misalignmentBuild governance, monitoring, and compliance systems for long-term successThis book focuses not on theory, but on real implementation-covering data readiness, infrastructure, clinical workflows, risk management, and continuous monitoring.With global case studies, practical frameworks, and step-by-step guidance, this is an essential resource for anyone involved in digital health, clinical AI, and healthcare innovation.Whether you are a doctor, data scientist, hospital administrator, policymaker, or health-tech entrepreneur, this book provides the tools to move from AI experimentation to safe, scalable, and impactful deployment in healthcare systems worldwide. 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 9798253272503
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