A machine learning model for mortality prediction in patients with severe fever with thrombocytopenia syndrome: a prospective, multicenter cohort study

A machine learning model for mortality prediction in patients with severe fever with thrombocytopenia syndrome: a prospective, multicenter cohort study

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease that imposes a considerable medical burden. In this study, we enrolled 1,606 SFTS patients, developed and validated machine learning models for mortality prediction, and ultimately constructed a model consisting of...

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Main Authors: Yanan Liu, Lei Fan, Wencai Wang, Hongxuan Song, Zhenhua Zhang, Qian Liu, Zhongji Meng, Shibo Li, Hua Wang, Shijun Zhou, Wanjun Liu, Guomei Xia, Jianping Duan, Chunxia Guo, Lu Wang, Ling Xu, Tong Wang, Hanxin Li, Xinyue Zhang, Tiandan Xiang, Di Liu, Zujiang Yu, Yuliang Liu, Junzhong Wang, Xin Zheng
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:Emerging Microbes and Infections
Subjects:
SFTS
bandavirus
early warning system
risk prediction model
machine learning
Online Access:https://www.tandfonline.com/doi/10.1080/22221751.2025.2498572
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https://www.tandfonline.com/doi/10.1080/22221751.2025.2498572

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