Ontology-driven weak supervision for clinical entity classification in electronic health records

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In the electronic health record, using clinical notes to identify entities such as disorders and their temporality (e.g. the order of an event relative to a time index) can inform many important analyses. However, creating training data for clinical entity tasks is time consuming and sharing labeled...

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Detalles Bibliográficos
Autores principales: Fries, Jason A., Steinberg, Ethan, Khattar, Saelig, Fleming, Scott L., Posada, Jose, Callahan, Alison, Shah, Nigam H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8016863/
https://www.ncbi.nlm.nih.gov/pubmed/33795682
http://dx.doi.org/10.1038/s41467-021-22328-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8016863/
https://www.ncbi.nlm.nih.gov/pubmed/33795682
http://dx.doi.org/10.1038/s41467-021-22328-4

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