Utilizing MRI Radiomics and Clinical Features to Predict Severe Acute Pancreatitis in Patients with Metabolic Syndrome
The combined model integrating MRI T2WI radiomics with clinical features provides robust and clinically valuable prediction of SAP in MetS patients, supporting its potential value for early clinical intervention.
Authors
- Xiaohua Huang (ORCID: https://orcid.org/0000-0002-3490-4142)
- Ziyi Liu (ORCID: https://orcid.org/0000-0002-6796-650X)
- Mengyue Tang
- Yuan Wang (ORCID: https://orcid.org/0000-0002-5215-0487)
- Xiaofeng Wan (ORCID: https://orcid.org/0000-0001-5301-8480)
- Yawen Zhang (ORCID: https://orcid.org/0009-0003-1699-1312)
- Ziyan Liu (ORCID: https://orcid.org/0000-0003-3992-9194)
Institutions
- Affiliated Hospital of North Sichuan Medical College (CN)
Publication Details
- Journal
- Journal of Inflammation Research
- Published
- 2025-11-01
- DOI
- https://doi.org/10.2147/jir.s539688
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Natural Science Foundation of Sichuan Province