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

BACKGROUND: Electronic 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 ascertainment of a patient’s medic...

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Detalles Bibliográficos
Autores principales: Moon, Sungrim, Carlson, Luke A, Moser, Ethan D, Agnikula Kshatriya, Bhavani Singh, Smith, Carin Y, Rocca, Walter A, Gazzuola Rocca, Liliana, Bielinski, Suzette J, Liu, Hongfang, Larson, Nicholas B
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2022
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8838563/
https://www.ncbi.nlm.nih.gov/pubmed/35089141
http://dx.doi.org/10.2196/29015

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8838563/
https://www.ncbi.nlm.nih.gov/pubmed/35089141
http://dx.doi.org/10.2196/29015

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