Predicting incidence of hepatitis E using machine learning in Jiangsu Province, China

Hepatitis E is an increasingly serious worldwide public health problem that has attracted extensive attention. It is necessary to accurately predict the incidence of hepatitis E to better plan ahead for future medical care. In this study, we developed a Bi-LSTM model that incorporated meteorological...

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Detalles Bibliográficos
Autores principales: Cheng, Xiaoqing, Liu, Wendong, Zhang, Xuefeng, Wang, Minghao, Bao, Changjun, Wu, Tianxing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2022
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9386790/
https://www.ncbi.nlm.nih.gov/pubmed/35899849
http://dx.doi.org/10.1017/S0950268822001303

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9386790/
https://www.ncbi.nlm.nih.gov/pubmed/35899849
http://dx.doi.org/10.1017/S0950268822001303

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