Deep learning radiomics analysis for prediction of survival in patients with unresectable gastric cancer receiving immunotherapy
The deep learning model in combination with several clinical factors showed predictive value for survival in patients with unresectable GC receiving immunotherapy.
Authors
- Niansong Qian (ORCID: https://orcid.org/0000-0002-3297-4294)
- Miaomiao Gou (ORCID: https://orcid.org/0000-0001-9622-1198)
- Zeyu Sun (ORCID: https://orcid.org/0000-0002-9990-9120)
- Zhikuan Wang (ORCID: https://orcid.org/0000-0002-7025-735X)
- Guang Li (ORCID: https://orcid.org/0000-0002-2340-4046)
- Yong Zhang
- Guanghai Dai (ORCID: https://orcid.org/0000-0002-7339-3840)
- Hongtao Zhang (ORCID: https://orcid.org/0000-0003-4182-421X)
Institutions
- Chinese PLA General Hospital (CN)
- 307th Hospital of Chinese People’s Liberation Army (CN)
- EA Technology (GB)
Publication Details
- Journal
- European Journal of Radiology Open
- Published
- 2024-12-19
- DOI
- https://doi.org/10.1016/j.ejro.2024.100626
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00