AI-assisted Radiomic Model for Cervical Cancer Recurrence Prediction: A Multicenter Retrospective Study with Experimental Validation
A nomogram integrating clinical, hematologic, and intratumoral and peritumoral MRI radiomic features predicted postoperative disease-free survival in cervical cancer, and a radiomic-TRIM29-cell cycle regulatory axis was identified.
Authors
- Yu Zhang (ORCID: https://orcid.org/0000-0002-5394-1686)
- Shuqing Chen
- Wei Yang (ORCID: https://orcid.org/0009-0000-6550-6406)
- Lei Chen (ORCID: https://orcid.org/0009-0003-5372-6577)
- Jun Dang
- Dong Chen
Institutions
- University of Science and Technology of China (CN)
- Anhui Medical University (CN)
- Fuyang City People's Hospital (CN)
- Chuzhou University (CN)
- First Affiliated Hospital of Anhui Medical University (CN)
- Fuyang Second People's Hospital (CN)
Publication Details
- Journal
- Radiology Imaging Cancer
- Published
- 2026-06-26
- DOI
- https://doi.org/10.1148/rycan.250618
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00