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08/13/26

Diagnostic accuracy of electronic medical record retrieval methods and a large language model for identifying cardiovascular events: a multisite retrospective validation study in a medical system in the United States.

Ibrahim, Omar; Farina, Juan; Pereyra Pietri, Milagros; Awad, Kamal; Abbas, Mohammed Tiseer; Scalia, Isabel G; Sheashaa, Hesham; Abdelfattah, Fatmaelzahraa E; Razaghi, Mahshad; Villa Etchegoyen, Cecilia C; Kaggal, Vinod C; Romero-Brufau, Santiago; Arsanjani, Reza; Ayoub, Chadi. BMJ Open.

Collection Topics
AI and Diagnosis Big Three Conditions Health IT Measurement, Monitoring, and Event Analysis
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Summary

Reliable identification of clinical events from electronic medical records (EMR) is essential for measuring diagnostic quality and outcomes. This multisite, retrospective, validation study compares EMR retrieval approaches, including a Gemini V.1.5 powered LLM, for identifying cardiovascular events. The study demonstrates potential efficiency gains in extracting diagnostic information, while emphasizing that improved information retrieval does not itself establish improved clinical diagnosis or patient outcomes.
Read the paper
Ibrahim O, Farina J, Pereyra Pietri M, et al. Diagnostic accuracy of electronic medical record retrieval methods and a large language model for identifying cardiovascular events: a multisite retrospective validation study in a medical system in the United States. BMJ Open. 2026;16(8):e116133.