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...

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Bibliografische gegevens
Gepubliceerd in:BMC Med Inform Decis Mak
Hoofdauteurs: 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
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: BioMed Central 2019
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Research
Online toegang:https://ncbi.nlm.nih.gov/pmc/articles/PMC6454598/
https://ncbi.nlm.nih.gov/pubmed/30961579
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12911-019-0766-3
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