Data Sheet 1_Enhancing fever of unknown origin diagnosis: machine learning approaches to predict metagenomic next-generation sequencing positivity.docx

Data Sheet 1_Enhancing fever of unknown origin diagnosis: machine learning approaches to predict metagenomic next-generation sequencing positivity.docx

Objective<p>Metagenomic next-generation sequencing (mNGS) can potentially detect various pathogenic microorganisms without bias to improve the diagnostic rate of fever of unknown origin (FUO), but there are no effective methods to predict mNGS-positive results. This study aimed to develop an i...

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Bibliographic Details
Main Author: Zhi Gao (257044) (author)
Other Authors: Yongfang Jiang (542422) (author), Mengxuan Chen (5873093) (author), Weihang Wang (19497138) (author), Qiyao Liu (16415116) (author), Jing Ma (24574) (author)
Published: 2025
Subjects:
Clinical Microbiology
metagenomic next-generation sequencing (mNGS)
fever of unknown origin (FUO)
machine learning algorithms
light gradient-boosting machine (LightGBM)
predictive modeling
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