Development of a respiratory virus risk model with environmental data based on interpretable machine learning methods
Abstract In recent years, numerous studies have explored the relationship between atmospheric conditions and respiratory viral infections. However, these investigations have faced certain limitations, such as the use of modestly sized datasets, a restricted geographical focus, and an emphasis on a l...
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Main Authors: | Shuting Shi, Haowen Lin, Leiming Jiang, Zhiqi Zeng, ChuiXu Lin, Pei Li, Yinghua Li, Zifeng Yang |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2025-02-01
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Series: | npj Climate and Atmospheric Science |
Online Access: | https://doi.org/10.1038/s41612-025-00894-4 |
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