Comparative Analysis of NLP Models for Automatic LOINC Document Ontology Named Entity Recognition in Clinical Note Titles.

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Bibliographic Details
Title: Comparative Analysis of NLP Models for Automatic LOINC Document Ontology Named Entity Recognition in Clinical Note Titles.
Authors: Bowles AE; VA Salt Lake City Health Care System.; Department of Internal Medicine, University of Utah Medical School, Salt Lake City, UT, USA., Gan Q; VA Salt Lake City Health Care System.; Department of Internal Medicine, University of Utah Medical School, Salt Lake City, UT, USA., Hanchrow E; VA Salt Lake City Health Care System.; Department of Internal Medicine, University of Utah Medical School, Salt Lake City, UT, USA., Duvall S; VA Salt Lake City Health Care System.; Department of Internal Medicine, University of Utah Medical School, Salt Lake City, UT, USA., Alba PR; VA Salt Lake City Health Care System.; Department of Internal Medicine, University of Utah Medical School, Salt Lake City, UT, USA., Shi J; VA Salt Lake City Health Care System.; Department of Internal Medicine, University of Utah Medical School, Salt Lake City, UT, USA.
Source: Studies in health technology and informatics [Stud Health Technol Inform] 2025 Aug 07; Vol. 329, pp. 769-773.
Publication Type: Journal Article; Comparative Study
Journal Info: Publisher: IOS Press Country of Publication: Netherlands NLM ID: 9214582 Publication Model: Print Cited Medium: Internet ISSN: 1879-8365 (Electronic) Linking ISSN: 09269630 NLM ISO Abbreviation: Stud Health Technol Inform Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1879-8365
DOI:10.3233/SHTI250944