XGBoost model for predicting erectile dysfunction risk after radical prostatectomy: development and validation using machine learning
The XGBoost model exhibited superior predictive performance and clinical applicability in assessing ED risk after radical prostatectomy, offering a robust tool for personalized postoperative management.
Authors
- Fei Mao (ORCID: https://orcid.org/0000-0001-5871-6878)
- Lü Ji
- Leilei Zhu (ORCID: https://orcid.org/0000-0001-9525-6639)
- Hesong Jiang
- Hengbing Wang (ORCID: https://orcid.org/0000-0002-1356-1080)
Institutions
- Wuxi People's Hospital (CN)
- Nanjing Medical University (CN)
Publication Details
- Journal
- Discover Oncology
- Published
- 2025-05-19
- DOI
- https://doi.org/10.1007/s12672-025-02685-y
- Citations
- 2
- Primary Topic
- Sexual function and dysfunction studies
- Type
- article
- Field-Weighted Citation Impact
- 2.94
Funders
- Xuzhou Medical University