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Dynamic Bayesian network in infectious diseases surveillance: a simulation study
The surveillance of infectious diseases relies on the identification of dynamic relations between the infectious diseases and corresponding influencing factors. However, the identification task confronts with two practical challenges: small sample size and delayed effect. To overcome both challenges...
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| Publicado no: | Sci Rep |
|---|---|
| Main Authors: | , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Nature Publishing Group UK
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6637193/ https://ncbi.nlm.nih.gov/pubmed/31316113 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-019-46737-0 |
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