This paper is in the following e-collection/theme issue:

Clinical Informatics (919) Electronic Health Records (971) Natural Language Processing (650) Obstetrics, Gynecology, and Reproductive Medicine (198) Clinical Information and Decision Making (1340)

Published on in Vol 24, No 1 (2022): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/29015, first published .
Identifying Information Gaps in Electronic Health Records by Using Natural Language Processing: Gynecologic Surgery History Identification

Identifying Information Gaps in Electronic Health Records by Using Natural Language Processing: Gynecologic Surgery History Identification

Identifying Information Gaps in Electronic Health Records by Using Natural Language Processing: Gynecologic Surgery History Identification

Authors of this article:

Sungrim Moon1 Author Orcid Image ;   Luke A Carlson1 Author Orcid Image ;   Ethan D Moser2 Author Orcid Image ;   Bhavani Singh Agnikula Kshatriya1 Author Orcid Image ;   Carin Y Smith3 Author Orcid Image ;   Walter A Rocca2, 4, 5 Author Orcid Image ;   Liliana Gazzuola Rocca2 Author Orcid Image ;   Suzette J Bielinski2 Author Orcid Image ;   Hongfang Liu1 Author Orcid Image ;   Nicholas B Larson3 Author Orcid Image
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