Enhancing cause of death prediction: development and validation of machine learning models using multimodal data across multiple health-care sites.

ABSTRACT:

Objectives

To develop and validate machine learning (ML) models that predict probable cause of death (CoD) using structured electronic health record (EHR) data, unstructured clinical notes, and publicly available sources.

Materials and methods

This multi-institutional retrospective study was conducted across Vanderbilt University Medical Center (VUMC) and Massachusetts General Brigham (MGB), including deceased patients with encounters between October 1, 2015, and January 1, 2021, and confirmed death records. The cohort included 13 708 patients from VUMC and 34 839 from MGB.The primary outcome was underlying CoD categorized into the top 15 National Center for Health Statistics rankable causes, with others grouped as "Other." Performance was assessed using weighted area under

SUBMITTER: Al-Garadi M 

PROVIDER: S-EPMC12924636 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature