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A clustering approach for detecting implausible observation values in electronic health records data
BACKGROUND: Identifying implausible clinical observations (e.g., laboratory test and vital sign values) in Electronic Health Record (EHR) data using rule-based procedures is challenging. Anomaly/outlier detection methods can be applied as an alternative algorithmic approach to flagging such implausi...
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| Publicado no: | BMC Med Inform Decis Mak |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
BioMed Central
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6652024/ https://ncbi.nlm.nih.gov/pubmed/31337390 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12911-019-0852-6 |
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