View in EDS

Natural language processing improves reliable identification of COVID-19 compared to diagnostic codes alone.

Saved in:
Bibliographic Details
Title: Natural language processing improves reliable identification of COVID-19 compared to diagnostic codes alone.
Authors: Hendrix N; Center for Professionalism and Value in Health Care, American Board of Family Medicine, Washington, DC 20036, United States., Parikh RV; Department of Epidemiology and Population Health, Stanford School of Medicine, Palo Alto, CA 94304, United States., Taskier M; Center for Professionalism and Value in Health Care, American Board of Family Medicine, Washington, DC 20036, United States., Walter G; Robert Graham Center, American Academy of Family Physicians, Washington, DC 20036, United States., Phillips RL; Center for Professionalism and Value in Health Care, American Board of Family Medicine, Washington, DC 20036, United States., Rehkopf DH; Department of Epidemiology and Population Health, Stanford School of Medicine, Palo Alto, CA 94304, United States.
Source: American journal of epidemiology [Am J Epidemiol] 2025 Nov 04; Vol. 194 (11), pp. 3348-3354.
Publication Type: Journal Article; Research Support, N.I.H., Extramural
Journal Info: Publisher: Oxford University Press Country of Publication: United States NLM ID: 7910653 Publication Model: Print Cited Medium: Internet ISSN: 1476-6256 (Electronic) Linking ISSN: 00029262 NLM ISO Abbreviation: Am J Epidemiol Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1476-6256
DOI:10.1093/aje/kwaf162