EHR2Vec: Representation Learning of Medical Concepts From Temporal Patterns of Clinical Notes Based on Self-Attention Mechanism

Efficiently learning representations of clinical concepts (i. e., symptoms, lab test, etc.) from unstructured clinical notes of electronic health record (EHR) data remain significant challenges, since each patient may have multiple visits at different times and each visit may contain different seque...

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Detalles Bibliográficos
Autores principales: Wang, Li, Wang, Qinghua, Bai, Heming, Liu, Cong, Liu, Wei, Zhang, Yuanpeng, Jiang, Lei, Xu, Huji, Wang, Kai, Zhou, Yunyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Genetics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7344186/
https://www.ncbi.nlm.nih.gov/pubmed/32714371
http://dx.doi.org/10.3389/fgene.2020.00630

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7344186/
https://www.ncbi.nlm.nih.gov/pubmed/32714371
http://dx.doi.org/10.3389/fgene.2020.00630

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