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Learning statistical models of phenotypes using noisy labeled training data
Objective Traditionally, patient groups with a phenotype are selected through rule-based definitions whose creation and validation are time-consuming. Machine learning approaches to electronic phenotyping are limited by the paucity of labeled training datasets. We demonstrate the feasibility of util...
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| Publicado no: | J Am Med Inform Assoc |
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| Main Authors: | , , , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Oxford University Press
2016
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5070523/ https://ncbi.nlm.nih.gov/pubmed/27174893 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/jamia/ocw028 |
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