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Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/81500, first published .
Doctor and patient discuss medical scans on tablet and laptop in clinic.

Large Language Model Automated Extraction of Clinical Signs and Symptoms From Emergency Department Reports for Machine Learning Prediction Models: Development and Validation Study

Large Language Model Automated Extraction of Clinical Signs and Symptoms From Emergency Department Reports for Machine Learning Prediction Models: Development and Validation Study

Journals

  1. Šuvalov H, Umov N, Malk M, Haug M, Laur S, Oja M, Tamm S, Reisberg S, Vilo J, Kolde R. Extracting and Classifying Drug Discontinuations From Estonian Electronic Health Records: Development and Validation Study. Journal of Medical Internet Research 2026;28:e86183 View
  2. Kwolek K, Laskowska W, Pilarek M, Ożga S, Roszkowska M, Furtak M, Janczarski S, Sarna D, Wąs Ł, Tryczyński P. GENERATIVE ARTIFICIAL INTELLIGENCE AND LARGE LANGUAGE MODELS IN EMERGENCY MEDICINE: A NARRATIVE REVIEW. International Journal of Innovative Technologies in Social Science 2026;1(3(51)) View
  3. Henn J, Stoll A, Feodorovici P, Subramani D, Röttgen J, Arensmeyer J, Gräff I, Wulff B, Kalff J, Matthaei H. Development and validation of a pragmatic pipeline for clinical free-text annotation using locally deployed open-weight large language models. Scientific Reports 2026;16(1) View
  4. Devisetti L, Chen B, Addo N, Narang K, Alvarez C, Kornak J, Singh C, Kornblith A. Automated Calculation of the Pediatric Emergency Care Applied Research Network (PECARN) Intra-Abdominal Injury Rule from Unstructured Emergency Department Notes Using a Large Language Model. JACEP Open 2026;7(6):100525 View