A machine learning model for robust prediction of sepsis-induced coagulopathy in critically ill patients with sepsis
We developed an optimal and operable ML model that was able to predict the risk of SIC in septic patients better than the SOFA scoring models.
Authors
- Guleng Siri (ORCID: https://orcid.org/0000-0003-0705-1153)
- Jia Sun (ORCID: https://orcid.org/0000-0003-4423-8128)
- Lixin Zhang (ORCID: https://orcid.org/0000-0003-1421-9612)
- Dan Wu (ORCID: https://orcid.org/0000-0001-8677-5867)
- Hongling Ma
- Ruo-Xi Wu (ORCID: https://orcid.org/0009-0008-2102-0381)
- Zhaotang Gong
Institutions
- Inner Mongolia People's Hospital (CN)
- Baotou Medical College (CN)
- Inner Mongolia Autonomous Region Hospital of Traditional Chinese Medicine (CN)
- Inner Mongolia Medical University (CN)
Publication Details
- Journal
- Frontiers in Cellular and Infection Microbiology
- Published
- 2025-06-06
- DOI
- https://doi.org/10.3389/fcimb.2025.1579558
- Citations
- 2
- Primary Topic
- Sepsis Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 2.71