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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Dettagli Bibliografici
Pubblicato in:JAMIA Open
Autori principali: Lee, Junghwan, Liu, Cong, Kim, Jae Hyun, Butler, Alex, Shang, Ning, Pang, Chao, Natarajan, Karthik, Ryan, Patrick, Ta, Casey, Weng, Chunhua
Natura: Artigo
Lingua:Inglês
Pubblicazione: Oxford University Press 2021
Soggetti:
Research and Applications
Accesso online: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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