Development of model for identifying homologous recombination deficiency (HRD) status of ovarian cancer with deep learning on whole slide images
The models we constructed enables accurate discrimination between tumor and non-tumor tissues in ovarian cancer as well as the prediction of HRD status for patients with ovarian cancer.
Authors
- Xiangxue Wang
- Yang Shen (ORCID: https://orcid.org/0000-0002-3313-5062)
- Yinghe Qiu (ORCID: https://orcid.org/0000-0002-2226-7668)
- Xiaoying Wei (ORCID: https://orcid.org/0000-0001-5665-209X)
- Yuxin Zhu (ORCID: https://orcid.org/0009-0006-0542-578X)
- Guoqing Wang (ORCID: https://orcid.org/0000-0001-9326-3755)
- Ke Zhang (ORCID: https://orcid.org/0000-0002-5973-6632)
- Qi Liu (ORCID: https://orcid.org/0000-0001-6956-5550)
- Han Yin (ORCID: https://orcid.org/0000-0003-2247-4306)
- Songwei Feng
- Haoyu Cui (ORCID: https://orcid.org/0009-0006-5745-0792)
Institutions
- Nanjing University of Information Science and Technology (CN)
- Zhongda Hospital Southeast University (CN)
Publication Details
- Journal
- Journal of Translational Medicine
- Published
- 2025-03-04
- DOI
- https://doi.org/10.1186/s12967-025-06234-7
- Citations
- 6
- Primary Topic
- PARP inhibition in cancer therapy
- Type
- article
- Field-Weighted Citation Impact
- 6.27
Funders
- National Natural Science Foundation of China