Construction of the preoperative staging prediction model for cervical cancer based on deep learning and MRI: a retrospective study
This study confirms that deep learning models utilizing MRI images can enable automated cervical cancer staging with improved accuracy and efficiency. HRNet, in particular, demonstrates strong potential as a clinical decision-support tool, contributing to the advancement of precision medicine and personalized treatment strategies for cervical cancer.
Authors
- Zhaoyang Ma (ORCID: https://orcid.org/0009-0006-5926-8783)
- Yingying Zhou
- Xiaoxian Ye
- Jiming Yang (ORCID: https://orcid.org/0000-0003-1648-3871)
- Xiaomin Dai (ORCID: https://orcid.org/0000-0003-4274-6225)
- Pengrong Lou
- Jiangping Ren
Institutions
- Ningbo University (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2025-04-02
- DOI
- https://doi.org/10.3389/fonc.2025.1557486
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00