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Utilizing large language models for detecting hospital-acquired conditions: an empirical study on pulmonary embolism

Author(s): Cheligeer C; Southern DA; Yan J; Wu G; Pan J; Lee S; Martin EA; Jafarpour H; Eastwood CA; Zeng Y; Quan H;

Objectives: Adverse event detection from Electronic Medical Records (EMRs) is challenging due to the low incidence of the event, variability in clinical documentation, and the complexity of data formats. Pulmonary embolism as an adverse event (PEAE) is particularly difficult to identify using exi ...

Article GUID: 40105654


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