The application of metagenomics, radiomics and machine learning for diagnosis of sepsis
This study provides insights into the relationship between microbes, metabolic pathways, and blood test indicators in sepsis. The developed machine learning model shows potential for aiding in clinical diagnosis. However, further research is needed to validate and improve the model.
Authors
- Lijuan Li (ORCID: https://orcid.org/0000-0002-2143-9560)
- Liyan Pan (ORCID: https://orcid.org/0000-0002-7306-4916)
- Wenyan Wu (ORCID: https://orcid.org/0000-0003-3907-1570)
- Shenshen Zhi
- Yuanyuan Zhang (ORCID: https://orcid.org/0000-0002-8159-1046)
- Xun Li (ORCID: https://orcid.org/0000-0002-1267-9263)
- Wei Li (ORCID: https://orcid.org/0009-0004-1347-9302)
- Xiefei Hu
- Yang Tao (ORCID: https://orcid.org/0009-0008-9457-8183)
- Haiping Fan
Institutions
- Chongqing University (CN)
- Chongqing Emergency Medical Center (CN)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2024-09-20
- DOI
- https://doi.org/10.3389/fmed.2024.1400166
- Citations
- 1
- Primary Topic
- Metabolomics and Mass Spectrometry Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.23
Funders
- Chongqing Municipal Education Commission