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Preprocessing narrative texts in electronic medical records to identify hospital adverse events: A scoping review

Author(s): Jafarpour H; Wu G; Cheligeer CK; Yan J; Xu Y; Southern DA; Eastwood CA; Zeng Y; Quan H;

Background: Narrative electronic medical records (EMR), which include textual notes created by clinicians within healthcare environments, represent a significant resource for documenting various facets of patient care. This form of text exhibits distinctive characteristics, such as the occurrence of grammatically incorrect sentences, abbreviations, freque ...

Article GUID: 41072367


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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