A generative deep neural network for pan-digestive tract cancer survival analysis
The experiment indicate that GDEC outperforms better than other deep-learning-based methods, and the interpretable algorithm can select biologically significant genes and potential drugs for DTC treatment.
Authors
- Hui Tang (ORCID: https://orcid.org/0000-0001-8856-9127)
- Lekai Xu
- Haotian Cao
- Tianjun Lan (ORCID: https://orcid.org/0000-0002-5680-6164)
- Xinpeng Song
- Hua Chai (ORCID: https://orcid.org/0000-0001-8354-3948)
- Yiqian Huang (ORCID: https://orcid.org/0009-0001-5601-3439)
- Liansheng Wang (ORCID: https://orcid.org/0000-0001-8070-5171)
- Junqi Lin
Institutions
- Foshan University (CN)
- Sun Yat-sen University (CN)
- Sun Yat-sen Memorial Hospital (CN)
Publication Details
- Journal
- BioData Mining
- Published
- 2025-01-27
- DOI
- https://doi.org/10.1186/s13040-025-00426-z
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Guangdong Province
- Foshan University