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Development and validation of phenotype classifiers across multiple sites in the observational health data sciences and informatics network
OBJECTIVE: Accurate electronic phenotyping is essential to support collaborative observational research. Supervised machine learning methods can be used to train phenotype classifiers in a high-throughput manner using imperfectly labeled data. We developed 10 phenotype classifiers using this approac...
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| Publié dans: | J Am Med Inform Assoc |
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| Auteurs principaux: | , , , , , , , |
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
Oxford University Press
2020
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| Sujets: | |
| Accès en ligne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7309227/ https://ncbi.nlm.nih.gov/pubmed/32374408 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/jamia/ocaa032 |
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