Predicting the prognosis of epithelial ovarian cancer patients based on deep learning models
This study successfully developed a nomogram and three machine learning models, which collectively served as important predictive instruments to support clinical decision making.
Authors
- Zhen Wang (ORCID: https://orcid.org/0000-0002-5765-0827)
- Zhihan Yao
- Xueting Bai
- Zhen Yang (ORCID: https://orcid.org/0000-0001-9763-6766)
- Yixin Zhang (ORCID: https://orcid.org/0000-0002-1146-8122)
- Qian Zhang (ORCID: https://orcid.org/0000-0002-0860-4023)
- Jiao Wang (ORCID: https://orcid.org/0000-0002-7883-0341)
- Wei Wu (ORCID: https://orcid.org/0000-0001-9992-2520)
- Zihan Li (ORCID: https://orcid.org/0000-0002-8670-1849)
- Yiming Yang (ORCID: https://orcid.org/0009-0006-3569-0023)
- Fanchen Zhou
- Rongxuan Xu
- Xiaofeng Li (ORCID: https://orcid.org/0000-0001-6033-9979)
Institutions
- Dalian Medical University (CN)
- Dalian Municipal Central Hospital (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2025-07-25
- DOI
- https://doi.org/10.3389/fonc.2025.1592746
- Citations
- 2
- Primary Topic
- Ovarian cancer diagnosis and treatment
- Type
- article
- Field-Weighted Citation Impact
- 3.40