Using Natural Language Processing to Improve Discrete Data Capture From Interpretive Cervical Biopsy Diagnoses at a Large Health Care Organization
Author:
Affiliation:
1. From Kaiser Permanente, TPMG Regional Laboratories, Berkeley, California (Wi, Goldhoff, Fuller, Grewal, Lorey).
2. From the Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland (Wentzensen, Clarke).
Abstract
Publisher
Archives of Pathology and Laboratory Medicine
Subject
Medical Laboratory Technology,General Medicine,Pathology and Forensic Medicine
Link
https://meridian.allenpress.com/aplm/article-pdf/147/2/222/3183718/i1543-2165-147-2-222.pdf
Reference18 articles.
1. United States Preventive Services Task Force (USPSTF) Cervical Cancer Screening, Recommendation: Cervical Cancer: Screening | United States Preventive Services Taskforce. uspreventiveservicestaskforce.org. Accessed July 30, 2021.
2. Waxman AG , ChelmowD, DarraghTM, LawsonH, MoscickiAB. Revised terminology for cervical histopathology and its implications for management of high-grade squamous intraepithelial lesions of the cervix. Obstet Gynecol. 2012;120(6):1465–1471.
3. Nayar R , WilburDC. The Bethesda System for Reporting Cervical Cytology: a historical perspective. Acta Cytol. 2017;61(4-5):359–372.
4. Nuno T , GarciaF. The LAST Project and its implications for clinical care. Obstet Gynecol Clin North Am. 2013;40(2):225–233.
5. Stoler MH , RonnettBM, JosteNE, HuntWC, CuzickJ, WheelerCM; New Mexico HPV Pap Registry Steering Committee. The interpretive variability of cervical biopsies and its relationship to HPV status. Am J Surg Pathol. 2015;39(6):729–736.
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