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
Article Authors Cited by (5) Tweetations (10) Metrics

Sungrim Moon   1 , PhD ;   Luke A Carlson   1 , BA ;   Ethan D Moser   2 , BS ;   Bhavani Singh Agnikula Kshatriya   1 , MS ;   Carin Y Smith   3 , BS ;   Walter A Rocca   2, 4, 5 , MD, MPH ;   Liliana Gazzuola Rocca   2 , MD ;   Suzette J Bielinski   2 , PhD ;   Hongfang Liu   1 , PhD ;   Nicholas B Larson   3 , PhD

1 Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, United States

2 Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, United States

3 Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, United States

4 Department of Neurology, Mayo Clinic, Rochester, MN, United States

5 Women’s Health Research Center, Mayo Clinic, Rochester, MN, United States

Corresponding Author:

  • Nicholas B Larson, PhD
  • Division of Clinical Trials and Biostatistics
  • Department of Quantitative Health Sciences
  • Mayo Clinic
  • 200 First Street SW
  • Rochester, MN, 55905
  • United States
  • Phone: 1 507-293-1700
  • Email: Larson.Nicholas@mayo.edu