AI4HF: Leveraging health informatics and epidemiologic data and methods for AI-based risk prediction and early intervention copertina

AI4HF: Leveraging health informatics and epidemiologic data and methods for AI-based risk prediction and early intervention

AI4HF: Leveraging health informatics and epidemiologic data and methods for AI-based risk prediction and early intervention

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In this episode of Cardio Talk Latest Research, Machteld Boonstra from Amsterdam University Medical Centre interviews Dr. Kazem Rahimi, Professor of Cardiovascular Medicine and Population Health at the University of Oxford, about how leveraging existing large-scale population health data from registries and biobanks offers a valuable approach to training and validating AI models for the early detection of congestive heart failure (CHF) deterioration.

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