Time-sensitive clinical concept embeddings learned from large electronic health records

BACKGROUND: Learning distributional representation of clinical concepts (e.g., diseases, drugs, and labs) is an important research area of deep learning in the medical domain. However, many existing relevant methods do not consider temporal dependencies along the longitudinal sequence of a patient’s...

Descripción completa

Detalles Bibliográficos
Autores principales: Xiang, Yang, Xu, Jun, Si, Yuqi, Li, Zhiheng, Rasmy, Laila, Zhou, Yujia, Tiryaki, Firat, Li, Fang, Zhang, Yaoyun, Wu, Yonghui, Jiang, Xiaoqian, Zheng, Wenjin Jim, Zhi, Degui, Tao, Cui, Xu, Hua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6454598/
https://www.ncbi.nlm.nih.gov/pubmed/30961579
http://dx.doi.org/10.1186/s12911-019-0766-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6454598/
https://www.ncbi.nlm.nih.gov/pubmed/30961579
http://dx.doi.org/10.1186/s12911-019-0766-3

Ejemplares similares