Natural language processing of electronic health records is superior to billing codes to identify symptom burden in hemodialysis patients.

Symptoms are common in patients on maintenance hemodialysis but identification is challenging. New informatics approaches including natural language processing (NLP) can be utilized to identify symptoms from narrative clinical documentation. Here we utilized NLP to identify seven patient symptoms fr...

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Detalhes bibliográficos
Publicado no:Kidney Int
Main Authors: Chan, Lili, Beers, Kelly, Yau, Amy, Chauhan, Kinsuk, Duffy, Aine, Chaudhary, Kumardeep, Debnath, Neha, Saha, Aparna, Pattharanitima, Pattharawin, Cho, Judy, Kotanko, Peter, Federman, Alex, Coca, Steven, Van Vleck, Tielman, Nadkarni, Girish N.
Formato: Artigo
Idioma:Inglês
Publicado em: 2019
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Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7001114/
https://ncbi.nlm.nih.gov/pubmed/31883805
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.kint.2019.10.023
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