Using Machine Learning to Predict the Prognosis in Endometrial Cancer Patients Undergoing Fertility‐Sparing Treatment
The integrated model effectively predicts fertility preservation outcomes, offering a reliable noninvasive tool for clinicians. This approach may enhance personalized treatment strategies for young endometrial cancer patients.
Authors
- Jianhong Liu (ORCID: https://orcid.org/0000-0003-3605-576X)
- Haidan Yin (ORCID: https://orcid.org/0009-0006-0072-1555)
- Ying Zheng (ORCID: https://orcid.org/0000-0002-7136-0113)
- Wenhan Yuan (ORCID: https://orcid.org/0009-0002-6249-159X)
Institutions
- Sichuan University (CN)
- Wuhan University (CN)
- West China Second University Hospital of Sichuan University (CN)
- State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing (CN)
Publication Details
- Journal
- Cancer Medicine
- Published
- 2025-11-01
- DOI
- https://doi.org/10.1002/cam4.71355
- Citations
- 1
- Primary Topic
- Endometrial and Cervical Cancer Treatments
- Type
- article
- Field-Weighted Citation Impact
- 2.06
Funders
- National Key Research and Development Program of China