A Machine Learning Model Integrating Preoperative Blood-Based Indices for Early and Noninvasive Detection of Endometrial Cancer
We developed and validated a GBDT prediction model, which showed the best performance in predicting endometrial cancer. This model can be applied in clinical practice to effectively predict the risk of EC for patients.
Authors
- J. Wang (ORCID: https://orcid.org/0000-0002-0070-1320)
- Jian Gu (ORCID: https://orcid.org/0000-0003-3499-0973)
- Y Wang (ORCID: https://orcid.org/0009-0005-2704-0840)
- Fei Wang (ORCID: https://orcid.org/0000-0003-3320-677X)
- HaoTian Wu
Institutions
- Sun Yat-sen University (CN)
- State Council of the People's Republic of China (CN)
- Third Affiliated Hospital of Sun Yat-sen University (CN)
Publication Details
- Journal
- Journal of Inflammation Research
- Published
- 2025-08-01
- DOI
- https://doi.org/10.2147/jir.s530974
- Primary Topic
- Endometrial and Cervical Cancer Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00