Article

Artificial Intelligence for Automated, Highly Accurate, and Scalable Multimodal EHR Data Abstraction

2026-03-17

Abstract excerpt

Electronic health records (EHRs) contain rich multimodal data but remain underutilized for populating clinical registries due to the time and cost of manual abstraction. We developed an AI-driven pipeline to automate data abstraction for variables in the Society of Thoracic Surgeons Adult Cardiac Surgery Database (ACSD). Models were developed using Mass General Brigham data and externally validated on Hartford Hea...

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Literature Corpus work: e18444cb-1e0d-586a-ba29-43701524a186
DOI: 10.64898/2026.03.16.26348522

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