Peritoneal cytology predicting distant metastasis in uterine carcinosarcoma: machine learning model development and validation
This study introduces the first effective tool for predicting distant metastasis in uterine carcinosarcoma patients by integrating peritoneal cytology features into model construction. It aids in early identification of high-risk patients, enhancing follow-up and monitoring during tumor development, and supports the optimization of personalized treatment strategies.
Authors
- Lilan Li (ORCID: https://orcid.org/0000-0002-0852-3661)
- Danru Chen
- Qi Guan (ORCID: https://orcid.org/0000-0002-6479-0510)
- Yibin Lin (ORCID: https://orcid.org/0000-0001-8177-8479)
- Qiaoming Lin
Institutions
- Fujian Medical University (CN)
Publication Details
- Journal
- World Journal of Surgical Oncology
- Published
- 2025-04-26
- DOI
- https://doi.org/10.1186/s12957-025-03771-9
- Primary Topic
- Endometrial and Cervical Cancer Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Natural Science Foundation of Fujian Province
- Fujian Provincial Health Commission