Computational Cardiology: Integrative Strategies for Disease Subtyping and Predict, an Issue of Heart Failure Clinics: Volume 23-1

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Bol In this issue of Heart Failure Clinics, guest editor Dr. Monica Franzese brings her considerable expertise to the topic of Computational Cardiology: Integrative Strategies for Disease Subtyping and Prediction. Computational cardiology integrates artificial intelligence, advanced imaging analysis, and mathematical modeling to transform cardiovascular medicine. In this issue, top experts address how computational approaches can enable precise risk stratification, personalized treatment strategies, and improved diagnostic accuracy across cardiovascular diseases. These methods are bridging complex data with actionable clinical insights, advancing precision medicine in cardiology. Contains 13 relevant, practice-oriented topics including advancements in quantitative echocardiology utilizing AI; statistical shape modeling in cardiology: bridging anatomy, mechanics, and pathophysiology; advances in AI-based cardiovascular disease prevention and assessment: a state-of-the-art review; and more. Provides in-depth clinical reviews on computational cardiology: integrative strategies for disease subtyping and prediction, offering actionable insights for clinical practice. Presents the latest information on this timely, focused topic under the leadership of experienced editors in the field. Authors synthesize and distill the latest research and practice guidelines to create clinically significant, topic-based reviews.

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In this issue of Heart Failure Clinics, guest editor Dr. Monica Franzese brings her considerable expertise to the topic of Computational Cardiology: Integrative Strategies for Disease Subtyping and Prediction. Computational cardiology integrates artificial intelligence, advanced imaging analysis, and mathematical modeling to transform cardiovascular medicine. In this issue, top experts address how computational approaches can enable precise risk stratification, personalized treatment strategies, and improved diagnostic accuracy across cardiovascular diseases. These methods are bridging complex data with actionable clinical insights, advancing precision medicine in cardiology. Contains 13 relevant, practice-oriented topics including advancements in quantitative echocardiology utilizing AI; statistical shape modeling in cardiology: bridging anatomy, mechanics, and pathophysiology; advances in AI-based cardiovascular disease prevention and assessment: a state-of-the-art review; and more. Provides in-depth clinical reviews on computational cardiology: integrative strategies for disease subtyping and prediction, offering actionable insights for clinical practice. Presents the latest information on this timely, focused topic under the leadership of experienced editors in the field. Authors synthesize and distill the latest research and practice guidelines to create clinically significant, topic-based reviews.

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Pagina's: 240, Hardcover, Churchill Livingstone


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  • 9780443472947
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