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Hidden Markov Model using Dirichlet Process for De-Identification
For the 2014 i2b2/UTHealth de-identification challenge, we introduced a new non-parametric Bayesian hidden Markov model using a Dirichlet Process (HMM-DP). The model intends to reduce task-specific feature engineering and to generalize well to new data. In the challenge we developed a variational me...
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| Publicado en: | J Biomed Inform |
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| Autores principales: | , , |
| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
2015
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| Materias: | |
| Acceso en línea: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4984397/ https://ncbi.nlm.nih.gov/pubmed/26407642 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.jbi.2015.09.004 |
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