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Machine Learning–Based Models Incorporating SDOH vs Traditional Models for Predicting In-Hospital Mortality For Heart Failure

Machine Learning–Based Models Incorporating SDOH vs Traditional Models for Predicting In-Hospital Mortality For Heart Failure

FromJAMA Cardiology Author Interviews


Machine Learning–Based Models Incorporating SDOH vs Traditional Models for Predicting In-Hospital Mortality For Heart Failure

FromJAMA Cardiology Author Interviews

ratings:
Length:
14 minutes
Released:
Jul 6, 2022
Format:
Podcast episode

Description

Interview with Ambarish Pandey, MD, MSCS, author of Machine Learning–Based Models Incorporating Social Determinants of Health vs Traditional Models for Predicting In-Hospital Mortality in Patients With Heart Failure, and Eldrin F. Lewis, MD, MPH, author of Machine Learning and Social Determinants of Health—An Opportunity to Move Beyond Race for Inpatient Risk Prediction in Patients With Heart Failure. Hosted by Clyde W. Yancy, MD. Related Content: Machine Learning–Based Models Incorporating Social Determinants of Health vs Traditional Models for Predicting In-Hospital Mortality in Patients With Heart Failure Machine Learning and Social Determinants of Health—An Opportunity to Move Beyond Race for Inpatient Risk Prediction in Patients With Heart Failure
Released:
Jul 6, 2022
Format:
Podcast episode

Titles in the series (100)

Interviews with authors of articles from JAMA Cardiology. JAMA Cardiology publishes exceptional original research, state-of-the-art reviews, and informative opinions that advance the science and practice of cardiology, enhance cardiovascular health, and inform health care policy. JAMA Cardiology is the definitive journal for clinical investigators, clinicians, and trainees in cardiovascular medicine worldwide. JAMA Cardiology focuses on all aspects of cardiovascular medicine, including epidemiology and prevention, diagnostic testing, interventional and pharmacologic therapeutics, translational research, health care policy and outcomes, and global health.