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JAMA Cardiology : Machine Learning–Based Models Incorporating SDOH vs Traditional Models for Predicting In-Hospital Mortality For Heart Failure
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
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By The JAMA Network
4.9
1212 ratings
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
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