A Random Survival Forest Model for Predicting Residual and Recurrent High-Grade Cervical Intraepithelial Neoplasia in Premenopausal Women
The RSF model outperformed the traditional Cox regression model in predicting residual and recurrent high-grade CIN risks post-LEEP. This model may be a more accurate clinical tool that facilitates improved personalized care and early interventions in gynecological oncology.
Authors
- Furui Zhai (ORCID: https://orcid.org/0000-0002-0365-3627)
- Ze Lv
- Yinghui Song (ORCID: https://orcid.org/0000-0002-6592-6678)
- Shanshan Mu (ORCID: https://orcid.org/0000-0003-3182-8559)
- Min Zhang (ORCID: https://orcid.org/0000-0002-4863-9431)
- Cui Zhang (ORCID: https://orcid.org/0000-0003-0886-6274)
Institutions
- Cangzhou Central Hospital (CN)
Publication Details
- Journal
- International Journal of Women s Health
- Published
- 2024-10-01
- DOI
- https://doi.org/10.2147/ijwh.s485515
- Citations
- 1
- Primary Topic
- Cervical Cancer and HPV Research
- Type
- article
- Field-Weighted Citation Impact
- 0.39