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Explainable Artificial Intelligence in Medical Decision Support Systems (Healthcare Technologies)
by Agbotiname Lucky Imoize (Editor), Jude Hemanth (Editor), Dinh-Thuan Do (Editor), Samarendra Nath Sur (Editor)
Medical decision support systems (MDSS) are computer-based programs that analyse data within a patient’s healthcare records to provide questions, prompts, or reminders to assist clinicians
at the point of care. Inputting a patient’s data, symptoms, or current treatment regimens into an MDSS, clinicians are assisted with the identification or elimination of the most likely
potential medical causes, which can enable faster discovery of a set of appropriate diagnoses or treatment plans. Explainable AI (XAI) is a “white box” model of artificial intelligence in
which the results of the solution can be understood by the users, who can see an estimate of the weighted importance of each feature on the model’s predictions, and understand how the
different features interact to arrive at a specific decision.
This book discusses XAI-based analytics for patient-specific MDSS as well as related security and privacy issues associated with processing patient data. It provides insights into real-world
scenarios of the deployment, application, management, and associated benefits of XAI in MDSS. The book outlines the frameworks for MDSS and explores the applicability, prospects, and legal
implications of XAI for MDSS. Applications of XAI in MDSS such as XAI for robot-assisted surgeries, medical image segmentation, cancer diagnostics, and diabetes mellitus and heart disease
prediction are explored.
You can buy this product at (Books Delivery) for home delivery and Cash on delivery to all over Pakistan. All kind of medical books are available.
Explainable Artificial Intelligence in Medical Decision Support Systems (Healthcare Technologies)
by Agbotiname Lucky Imoize (Editor), Jude Hemanth (Editor), Dinh-Thuan Do (Editor), Samarendra Nath Sur (Editor)
Medical decision support systems (MDSS) are computer-based programs that analyse data within a patient’s healthcare records to provide questions, prompts, or reminders to assist clinicians
at the point of care. Inputting a patient’s data, symptoms, or current treatment regimens into an MDSS, clinicians are assisted with the identification or elimination of the most likely
potential medical causes, which can enable faster discovery of a set of appropriate diagnoses or treatment plans. Explainable AI (XAI) is a “white box” model of artificial intelligence in
which the results of the solution can be understood by the users, who can see an estimate of the weighted importance of each feature on the model’s predictions, and understand how the
different features interact to arrive at a specific decision.
This book discusses XAI-based analytics for patient-specific MDSS as well as related security and privacy issues associated with processing patient data. It provides insights into real-world
scenarios of the deployment, application, management, and associated benefits of XAI in MDSS. The book outlines the frameworks for MDSS and explores the applicability, prospects, and legal
implications of XAI for MDSS. Applications of XAI in MDSS such as XAI for robot-assisted surgeries, medical image segmentation, cancer diagnostics, and diabetes mellitus and heart disease
prediction are explored.
You can buy this product at (Books Delivery) for home delivery and Cash on delivery to all over Pakistan. All kind of medical books are available.
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