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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...
| Autores principales: | , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Oxford University Press
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7309227/ https://www.ncbi.nlm.nih.gov/pubmed/32374408 http://dx.doi.org/10.1093/jamia/ocaa032 |