Machine Learning Predictive Models for Survival in Gastric Cancer Patients with Diabetes: A Population-Based Cohort Study
This study enhances our understanding of gastric cancer prognosis in patients with T2DM by identifying significant risk factors and developing risk-scoring systems. Further research is needed to elucidate the underlying mechanisms of these risk factors and to validate the risk-scoring systems in clinical settings.
Authors
- Jonathan Poon
- Martin C. S. Wong (ORCID: https://orcid.org/0000-0001-7706-9370)
- Junjie Huang (ORCID: https://orcid.org/0000-0003-2382-4443)
- Qi Dou (ORCID: https://orcid.org/0000-0002-3416-9950)
- Yu Jiang (ORCID: https://orcid.org/0000-0001-7036-0384)
- Zhaojun Li (ORCID: https://orcid.org/0000-0001-6459-3667)
- Jinqiu Yuan (ORCID: https://orcid.org/0000-0002-7947-2646)
- Claire Chenwen Zhong
- Zehuan Yang
Institutions
- Hospital Authority (HK)
- Department of Health (CN)
- Sun Yat-sen University (CN)
- Chinese University of Hong Kong (HK)
- Education University of Hong Kong (HK)
- The Seventh Affiliated Hospital of Sun Yat-sen University (CN)
- Hong Kong Jockey Club (HK)
Publication Details
- Journal
- Oncology
- Published
- 2025-09-04
- DOI
- https://doi.org/10.1159/000548220
- Primary Topic
- Gastric Cancer Management and Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 0.00