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In recent years, the healthcare industry has witnessed a rapid integration of artificial intelligence (AI) into various aspects of patient care, diagnosis, treatment, and management. The promise of improved efficiency, accuracy, and personalized healthcare has spurred the development and adoption of AI technologies. However, this rapid advancement has brought forth numerous ethical challenges, privacy concerns, and the need for responsible governance. The increasing reliance on AI in medical analytics raises questions about patient data privacy, algorithmic bias, transparency, and the overall impact on the doctor-patient relationship. The urgency to balance innovation with ethical considerations is underscored by high-profile incidents of AI system failures, biased algorithms, and potential risks to patient safety. As technology advances, further research is necessary to showcase the possibilities of AI while navigating the complexities of responsible implementation. Responsible AI for Digital Health and Medical Analytics explores the transformative potential of AI while placing a crucial emphasis on responsible and ethical practices. It decodes complex medical analytics and examines patient privacy solutions to overcome ethical challenges. This book covers topics such as blockchain, medical diagnosis and prediction, and personalized medicine, and is a useful resource for healthcare professionals, policymakers, data scientists, computer engineers, academicians, and researchers.
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Paperback. Condizione: new. Paperback. In recent years, the healthcare industry has witnessed a rapid integration of artificial intelligence (AI) into various aspects of patient care, diagnosis, treatment, and management. The promise of improved efficiency, accuracy, and personalized healthcare has spurred the development and adoption of AI technologies. However, this rapid advancement has brought forth numerous ethical challenges, privacy concerns, and the need for responsible governance. The increasing reliance on AI in medical analytics raises questions about patient data privacy, algorithmic bias, transparency, and the overall impact on the doctor-patient relationship. The urgency to balance innovation with ethical considerations is underscored by high-profile incidents of AI system failures, biased algorithms, and potential risks to patient safety. As technology advances, further research is necessary to showcase the possibilities of AI while navigating the complexities of responsible implementation. Responsible AI for Digital Health and Medical Analytics explores the transformative potential of AI while placing a crucial emphasis on responsible and ethical practices. It decodes complex medical analytics and examines patient privacy solutions to overcome ethical challenges. This book covers topics such as blockchain, medical diagnosis and prediction, and personalized medicine, and is a useful resource for healthcare professionals, policymakers, data scientists, computer engineers, academicians, and researchers. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9798337309743
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Responsible AI for Digital Health and Medical Analytics (Paperback)
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Paperback. Condizione: new. Paperback. In recent years, the healthcare industry has witnessed a rapid integration of artificial intelligence (AI) into various aspects of patient care, diagnosis, treatment, and management. The promise of improved efficiency, accuracy, and personalized healthcare has spurred the development and adoption of AI technologies. However, this rapid advancement has brought forth numerous ethical challenges, privacy concerns, and the need for responsible governance. The increasing reliance on AI in medical analytics raises questions about patient data privacy, algorithmic bias, transparency, and the overall impact on the doctor-patient relationship. The urgency to balance innovation with ethical considerations is underscored by high-profile incidents of AI system failures, biased algorithms, and potential risks to patient safety. As technology advances, further research is necessary to showcase the possibilities of AI while navigating the complexities of responsible implementation. Responsible AI for Digital Health and Medical Analytics explores the transformative potential of AI while placing a crucial emphasis on responsible and ethical practices. It decodes complex medical analytics and examines patient privacy solutions to overcome ethical challenges. This book covers topics such as blockchain, medical diagnosis and prediction, and personalized medicine, and is a useful resource for healthcare professionals, policymakers, data scientists, computer engineers, academicians, and researchers. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9798337309743
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Responsible AI for Digital Health and Medical Analytics (Paperback)
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Paperback. Condizione: new. Paperback. In recent years, the healthcare industry has witnessed a rapid integration of artificial intelligence (AI) into various aspects of patient care, diagnosis, treatment, and management. The promise of improved efficiency, accuracy, and personalized healthcare has spurred the development and adoption of AI technologies. However, this rapid advancement has brought forth numerous ethical challenges, privacy concerns, and the need for responsible governance. The increasing reliance on AI in medical analytics raises questions about patient data privacy, algorithmic bias, transparency, and the overall impact on the doctor-patient relationship. The urgency to balance innovation with ethical considerations is underscored by high-profile incidents of AI system failures, biased algorithms, and potential risks to patient safety. As technology advances, further research is necessary to showcase the possibilities of AI while navigating the complexities of responsible implementation. Responsible AI for Digital Health and Medical Analytics explores the transformative potential of AI while placing a crucial emphasis on responsible and ethical practices. It decodes complex medical analytics and examines patient privacy solutions to overcome ethical challenges. This book covers topics such as blockchain, medical diagnosis and prediction, and personalized medicine, and is a useful resource for healthcare professionals, policymakers, data scientists, computer engineers, academicians, and researchers. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Codice articolo 9798337309743
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Responsible AI for Digital Health and Medical Analytics
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In recent years, the healthcare industry has witnessed a rapid integration of artificial intelligence (AI) into various aspects of patient care, diagnosis, treatment, and management. The promise of improved efficiency, accuracy, and personalized healthcare has spurred the development and adoption of AI technologies. However, this rapid advancement has brought forth numerous ethical challenges, privacy concerns, and the need for responsible governance. The increasing reliance on AI in medical analytics raises questions about patient data privacy, algorithmic bias, transparency, and the overall impact on the doctor-patient relationship. The urgency to balance innovation with ethical considerations is underscored by high-profile incidents of AI system failures, biased algorithms, and potential risks to patient safety. As technology advances, further research is necessary to showcase the possibilities of AI while navigating the complexities of responsible implementation. Responsible AI for Digital Health and Medical Analytics explores the transformative potential of AI while placing a crucial emphasis on responsible and ethical practices. It decodes complex medical analytics and examines patient privacy solutions to overcome ethical challenges. This book covers topics such as blockchain, medical diagnosis and prediction, and personalized medicine, and is a useful resource for healthcare professionals, policymakers, data scientists, computer engineers, academicians, and researchers. Codice articolo 9798337309743
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