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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Detalles Bibliográficos
Autores principales: Lee, Junghwan, Liu, Cong, Kim, Jae Hyun, Butler, Alex, Shang, Ning, Pang, Chao, Natarajan, Karthik, Ryan, Patrick, Ta, Casey, Weng, Chunhua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Research and Applications
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8206403/
https://www.ncbi.nlm.nih.gov/pubmed/34142015
http://dx.doi.org/10.1093/jamiaopen/ooab028

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8206403/
https://www.ncbi.nlm.nih.gov/pubmed/34142015
http://dx.doi.org/10.1093/jamiaopen/ooab028

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