Enhancing fever of unknown origin diagnosis: machine learning approaches to predict metagenomic next-generation sequencing positivity
The validated LightGBM-based predictive model could have practical clinical value in enhancing the application of mNGS in the etiological diagnosis of FUO, representing a powerful tool to optimize the timing of mNGS.
Authors
- Jing Ma (ORCID: https://orcid.org/0000-0001-6286-8153)
- Zhi Gao (ORCID: https://orcid.org/0000-0003-3325-1183)
- Weihang Wang (ORCID: https://orcid.org/0000-0002-0628-5532)
- Mengxuan Chen (ORCID: https://orcid.org/0000-0001-9676-4598)
- Yongfang Jiang (ORCID: https://orcid.org/0000-0003-3880-0583)
- Qiyao Liu (ORCID: https://orcid.org/0000-0002-7657-6167)
Institutions
- Central South University (CN)
- Second Xiangya Hospital of Central South University (CN)
- Education Department of Hunan Province (CN)
Publication Details
- Journal
- Frontiers in Cellular and Infection Microbiology
- Published
- 2025-04-15
- DOI
- https://doi.org/10.3389/fcimb.2025.1550933
- Citations
- 1
- Primary Topic
- Hematological disorders and diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 2.25
Funders
- National Natural Science Foundation of China