Predicting the prognosis of epithelial ovarian cancer patients based on deep learning models
BackgroundEpithelial ovarian cancer(EOC) has a higher mortality and morbidity rate than other types, and it has a dramatic impact on the survival of ovarian cancer(OC) patients. Therefore, investigating, developing and validating prognostic models to predict overall survival(OS) in patients with epi...
Saved in:
| Main Authors: | Zihan Li, Jiao Wang, Yixin Zhang, Zhen Yang, Fanchen Zhou, Xueting Bai, Qian Zhang, Wenchong Zhen, Rongxuan Xu, Wei Wu, Zhihan Yao, Xiaofeng Li, Yiming Yang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-07-01
|
| Series: | Frontiers in Oncology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2025.1592746/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Deep learning based on ultrasound images to predict platinum resistance in patients with epithelial ovarian cancer
by: Chang Su, et al.
Published: (2025-05-01) -
Functional validation of somatic variability in TP53 and KRAS for prediction of platinum sensitivity and prognosis in epithelial ovarian carcinoma patients
by: Al Obeed Allah Mohammad, et al.
Published: (2025-12-01) -
Immunohistochemical Expression of p53 in Epithelial Ovarian Carcinoma and Its Correlation with Clinicopathological Parameters
by: Farzana Sharmin, et al. -
Survival Outcomes in Epithelial Ovarian Cancer: The Role of the Ovarian Cancer-specific Comorbidity Index
by: İrem Küçükşahin, et al.
Published: (2025-08-01) -
Prognostic and Predictive Value of Systemic Inflammatory Markers in Epithelial Ovarian Cancer
by: Cem İdrisoğlu, et al.
Published: (2025-02-01)