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