Development and validation of a machine learning model based on multiple kernel for predicting the recurrence risk of Budd-Chiari syndrome
This study identifies risk factors influencing BCS recurrence and validates the MKSVRB model as a significant advancement over existing prediction methods. The model exhibits strong potential for early detection, risk stratification, and recurrence prevention in BCS patients.
Authors
- Guo‐Ping Zhou (ORCID: https://orcid.org/0000-0002-1140-2481)
- Xiaoxiao Zhu (ORCID: https://orcid.org/0000-0002-7086-4256)
- Yingliang Jin (ORCID: https://orcid.org/0000-0001-9346-4936)
- Shengli Li (ORCID: https://orcid.org/0000-0003-0570-4165)
- Jia-Jia Qin (ORCID: https://orcid.org/0009-0000-5370-4472)
- Peilin Yu
- Weirong Xue
- Hui Wang (ORCID: https://orcid.org/0000-0001-8478-9990)
Institutions
- Xuzhou Medical College (CN)
- Xuzhou Central Hospital (CN)
Publication Details
- Journal
- Frontiers in Physiology
- Published
- 2025-05-30
- DOI
- https://doi.org/10.3389/fphys.2025.1589469
- Citations
- 1
- Primary Topic
- Liver Disease Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 1.35