Explainable Machine Learning Model for Predicting Postoperative Survival in Patients With Locally Advanced Gastric Cancer
This study developed an RSF-based model to predict postoperative survival in LAGC patients, emphasizing the prognostic significance of LNR, AJCC stage, and age. The interactive prediction tool enhances clinical utility, facilitating personalized treatment decision-making for physicians.
Authors
- Qiangbang Yang
- Jun Zhou (ORCID: https://orcid.org/0009-0008-7533-8926)
- Yingze Li (ORCID: https://orcid.org/0009-0005-9035-7218)
- Jian Pan (ORCID: https://orcid.org/0000-0002-6845-8486)
- Weiwei Wang (ORCID: https://orcid.org/0000-0002-8478-1021)
- Yinghao He
- Ming-Hui Ma (ORCID: https://orcid.org/0000-0002-2566-0932)
- Xiaolu Yuan (ORCID: https://orcid.org/0000-0003-3902-5013)
- Yanjie Deng
- Liping Zhou (ORCID: https://orcid.org/0000-0002-5670-2373)
- Zhijie Gong (ORCID: https://orcid.org/0009-0004-9767-9423)
Institutions
- Guangdong Medical College (CN)
- University of Qom (IR)
- Boxing People's Hospital (CN)
- Southern Medical University (CN)
Publication Details
- Journal
- Cancer Medicine
- Published
- 2025-11-01
- DOI
- https://doi.org/10.1002/cam4.71408
- Citations
- 1
- Primary Topic
- Gastric Cancer Management and Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 1.52