Improving the precision of modeling the incidence of hemorrhagic fever with renal syndrome in mainland China with an ensemble machine learning approach.

Improving the precision of modeling the incidence of hemorrhagic fever with renal syndrome in mainland China with an ensemble machine learning approach.

<h4>Objective</h4>Hemorrhagic fever with renal syndrome (HFRS), one of the main public health concerns in mainland China, is a group of clinically similar diseases caused by hantaviruses. Statistical approaches have always been leveraged to forecast the future incidence rates of certain...

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Bibliographic Details
Main Authors: Guo-Hua Ye, Mirxat Alim, Peng Guan, De-Sheng Huang, Bao-Sen Zhou, Wei Wu
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2021-01-01
Series:PLoS ONE
Online Access:https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0248597&type=printable
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https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0248597&type=printable

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