CT deep learning radiomics and genomics for predicting staging of epithelial ovarian cancer

The combined model can successfully predict staging in patients with EOC, providing reliable basis to develop personalized treatment strategies for EOC patients.

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Publication Details

Journal
International Journal of Surgery
Published
2026-01-19
DOI
https://doi.org/10.1097/js9.0000000000004924
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00
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article

CT deep learning radiomics and genomics for predicting staging of epithelial ovarian cancer

Fengyuan Luo, Yinping Leng, Pei Yang, Xiao Yu et al.
International Journal of Surgery
Radiomics and Machine Learning in Medical Imaging
article

CT deep learning radiomics and genomics for predicting staging of epithelial ovarian cancer

Fengyuan Luo, Yinping Leng, Pei Yang, Xiao Yu, Wanling Qi, Mengyao Hu, Yu Wang, Fei Peng, Wenjie Liu, Lianggeng Gong
article en

Abstract

The combined model can successfully predict staging in patients with EOC, providing reliable basis to develop personalized treatment strategies for EOC patients.

International Journal of Surgery
Nanchang University (CN), Philips (China) (CN), First Affiliated Hospital of Jiangxi Medical College (CN), Jiangxi Provincial People's Hospital (CN), Second Affiliated Hospital of Nanchang University (CN), University of South China (CN)
Openalex Percentile: Top 84%
Radiomics and Machine Learning in Medical Imaging
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CT deep learning radiomics and genomics for predicting staging of epithelial ovarian cancer — Fengyuan Luo, Yinping Leng, et al. · International Journal of Surgery (2026) | TGRS Research Map | TGRS