Polar labeling: silver standard algorithm for training disease classifiers

MOTIVATION: Expert-labeled data are essential to train phenotyping algorithms for cohort identification. However expert labeling is time and labor intensive, and the costs remain prohibitive for scaling phenotyping to wider use-cases. RESULTS: We present an approach referred to as polar labeling (PL...

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Detalles Bibliográficos
Autores principales: Wagholikar, Kavishwar B, Estiri, Hossein, Murphy, Marykate, Murphy, Shawn N
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Original Papers
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7214041/
https://www.ncbi.nlm.nih.gov/pubmed/32049335
http://dx.doi.org/10.1093/bioinformatics/btaa088

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7214041/
https://www.ncbi.nlm.nih.gov/pubmed/32049335
http://dx.doi.org/10.1093/bioinformatics/btaa088

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