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

BackgroundElectronic health records (EHRs) are a rich source of longitudinal patient data. However, missing information due to clinical care that predated the implementation of EHR system(s) or care that occurred at different medical institutions impedes complete ascertainmen...

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Bibliographic Details
Main Authors: Sungrim Moon, Luke A Carlson, Ethan D Moser, Bhavani Singh Agnikula Kshatriya, Carin Y Smith, Walter A Rocca, Liliana Gazzuola Rocca, Suzette J Bielinski, Hongfang Liu, Nicholas B Larson
Format: Article
Language:English
Published: JMIR Publications 2022-01-01
Series:Journal of Medical Internet Research
Online Access:https://www.jmir.org/2022/1/e29015

Internet

https://www.jmir.org/2022/1/e29015

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