A risk prediction model for recurrence in patients with borderline ovarian tumor based on artificial neural network: development and validation study
The N-MTLR neural network enables superior nonlinear modeling of BOT recurrence risk, exhibits excellent temporal and spatial generalizability, which supports precise risk stratification for clinical decision-making.
Authors
- Chi Fei
- Yuexin Hu (ORCID: https://orcid.org/0000-0002-7829-1421)
- Xiao Li (ORCID: https://orcid.org/0000-0002-7078-9815)
- Qiulin Ye
- Bei Lin (ORCID: https://orcid.org/0000-0002-8881-9859)
- Aimin Liu (ORCID: https://orcid.org/0000-0003-1634-8821)
- Juanjuan Liu (ORCID: https://orcid.org/0009-0005-5147-5633)
- Yue Qi (ORCID: https://orcid.org/0000-0003-0007-2373)
- Dongying Wang (ORCID: https://orcid.org/0009-0001-9114-3140)
- Tianmin Xu
Institutions
- Jilin University (CN)
- Second Affiliated Hospital of Jilin University (CN)
- China Medical University (CN)
Publication Details
- Journal
- Journal of Ovarian Research
- Published
- 2025-12-10
- DOI
- https://doi.org/10.1186/s13048-025-01920-y
- Primary Topic
- Ovarian cancer diagnosis and treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00