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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Detalles Bibliográficos
Autores principales: Zhang, Tao, Ma, Yue, Xiao, Xiong, Lin, Yun, Zhang, Xingyu, Yin, Fei, Li, Xiaosong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6637193/
https://www.ncbi.nlm.nih.gov/pubmed/31316113
http://dx.doi.org/10.1038/s41598-019-46737-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6637193/
https://www.ncbi.nlm.nih.gov/pubmed/31316113
http://dx.doi.org/10.1038/s41598-019-46737-0

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