Relevant Word Order Vectorization for Improved Natural Language Processing in Electronic Health Records

Electronic health records (EHR) represent a rich resource for conducting observational studies, supporting clinical trials, and more. However, much of the data contains unstructured text, presenting an obstacle to automated extraction. Natural language processing (NLP) can structure and learn from t...

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Detalles Bibliográficos
Autores principales: Thompson, Jeffrey, Hu, Jinxiang, Mudaranthakam, Dinesh Pal, Streeter, David, Neums, Lisa, Park, Michele, Koestler, Devin C., Gajewski, Byron, Jensen, Roy, Mayo, Matthew S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6592944/
https://www.ncbi.nlm.nih.gov/pubmed/31239489
http://dx.doi.org/10.1038/s41598-019-45705-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6592944/
https://www.ncbi.nlm.nih.gov/pubmed/31239489
http://dx.doi.org/10.1038/s41598-019-45705-y

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