Integrating transcriptomic data and digital pathology for NRG-based prediction of prognosis and therapy response in gastric cancer
The NRG signature and its deep learning model have significant clinical implications, highlighting the importance of individualized treatment strategies based on GC subtyping. These findings provide valuable insights for guiding clinical decision-making and treatment approaches for GC.
Authors
- Zhiyi Ye (ORCID: https://orcid.org/0000-0003-0285-7502)
- Jingjing Jing
- Xu Zhao (ORCID: https://orcid.org/0000-0002-0233-9660)
- Wei Zheng (ORCID: https://orcid.org/0000-0003-3193-2655)
- Qiuyan Sun
- Tan Li
Institutions
- Liaoning Vocational College of Medical (CN)
- First Hospital of China Medical University (CN)
- China Medical University (CN)
Publication Details
- Journal
- Annals of Medicine
- Published
- 2024-11-11
- DOI
- https://doi.org/10.1080/07853890.2024.2426758
- Citations
- 5
- Primary Topic
- Cancer-related molecular mechanisms research
- Type
- article
- Field-Weighted Citation Impact
- 1.43
Funders
- Department of Science and Technology of Liaoning Province