Use of a Large Language Model to Identify and Classify Injuries With Free-Text Emergency Department Data
Giulia Lorenzoni, Darío Gregori, Silvia Bressan, Honoria Ocagli, Danila Azzolina, Liviana Da Dalt, Paola Berchialla
Abstract
This cross-sectional study assesses the accuracy, sensitivity, and specificity of a large language model used to process unstructured, non-English emergency department (ED) data in medical records.
Topics & Concepts
Emergency departmentText messagingComputer scienceMedical emergencyNatural language processingUnstructured dataMedical recordMedicineArtificial intelligenceData miningWorld Wide WebBig dataRadiologyNursingEmergency and Acute Care StudiesNursing Diagnosis and Documentation