Comparative effectiveness of medical concept embedding for feature engineering in phenotyping

OBJECTIVE: Feature engineering is a major bottleneck in phenotyping. Properly learned medical concept embeddings (MCEs) capture the semantics of medical concepts, thus are useful for retrieving relevant medical features in phenotyping tasks. We compared the effectiveness of MCEs learned from knowled...

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Detalhes bibliográficos
Publicado no:JAMIA Open
Main Authors: Lee, Junghwan, Liu, Cong, Kim, Jae Hyun, Butler, Alex, Shang, Ning, Pang, Chao, Natarajan, Karthik, Ryan, Patrick, Ta, Casey, Weng, Chunhua
Formato: Artigo
Idioma:Inglês
Publicado em: Oxford University Press 2021
Assuntos:
Research and Applications
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC8206403/
https://ncbi.nlm.nih.gov/pubmed/34142015
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/jamiaopen/ooab028
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