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Patient Clustering with Uncoded Text in Electronic Medical Records
We propose a mixture model for text data designed to capture underlying structure in the history of present illness section of electronic medical records data. Additionally, we propose a method to induce bias that leads to more homogeneous sets of diagnoses for patients in each cluster. We apply our...
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| Main Authors: | , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
American Medical Informatics Association
2013
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3900202/ https://ncbi.nlm.nih.gov/pubmed/24551361 |
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