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Predicting Causes of Death from Structured Electronic Health Records Using Machine Learning

    Basic Details
    Date
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    Presentation
    Description

    Rapidly identifying causes of death (CoD) is important for the surveillance of medical products but is limited by the delayed availability of cause of death information for patients.  Structured electronic health record (EHR) data represents a rich source of patient medical history and care delivery information but has significant variability.  

    This presentation evaluates the capacity of machine learning (ML) using structured EHR data to predict CoD. It was presented at the 2024 ISPE Annual Meeting.
     

    Presenter(s)

    Mohammed A. Al-Garadi, Ruth Reeves, Rishi J. Desai, Michele LeNoue-Newton, Daniel Park, Shirley V. Wang, Judith C. Maro, Candace Fuller, Kueiyu Joshua Lin, Jose J. Hernández-Muñoz, Aida Kuzucan, Xi Wang, Haritha Pillai, Kerry Ngan, Jill Whitaker, Jessica A. Deere, Michael F. McLemore, Dax Westerman, Michael E. Matheny