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Comparison of rule- and large language model-based phenotype extraction from clinical notes for neurofibromatosis type 1.

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Bibliographic Details
Title: Comparison of rule- and large language model-based phenotype extraction from clinical notes for neurofibromatosis type 1.
Authors: Kaster L; Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine in St Louis, St Louis, MO 63110, United States., Hillis E; Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine in St Louis, St Louis, MO 63110, United States., Oh IY; Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine in St Louis, St Louis, MO 63110, United States., Cordell EC; Department of Neurology, Washington University School of Medicine in St Louis, St Louis, MO 63110, United States., Foraker RE; Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine in St Louis, St Louis, MO 63110, United States., Lai AM; Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine in St Louis, St Louis, MO 63110, United States., Morris SM; Center for Autism Services, Science, and Innovation (CASSI), Kennedy Krieger Institute, Baltimore, MD 21211, United States., Gutmann DH; Department of Neurology, Washington University School of Medicine in St Louis, St Louis, MO 63110, United States., Payne PRO; Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine in St Louis, St Louis, MO 63110, United States., Gupta A; Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine in St Louis, St Louis, MO 63110, United States.
Source: Journal of the American Medical Informatics Association : JAMIA [J Am Med Inform Assoc] 2025 Nov 01; Vol. 32 (11), pp. 1663-1673.
Publication Type: Journal Article; Comparative Study
Journal Info: Publisher: Oxford University Press Country of Publication: England NLM ID: 9430800 Publication Model: Print Cited Medium: Internet ISSN: 1527-974X (Electronic) Linking ISSN: 10675027 NLM ISO Abbreviation: J Am Med Inform Assoc Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1527-974X
DOI:10.1093/jamia/ocaf155