A machine learning approach to risk-stratification of gastric cancer based on tumour-infiltrating immune cell profiles
Background Gastric cancer (GC) is a highly heterogeneous disease, and the response of patients to clinical treatment varies substantially. There is no satisfactory strategy for predicting curative effects to date. We aimed to explore a new method for predicting the clinical efficacy of GC treatment...
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| Main Authors: | Yanping Hu, Bo Wang, Chao Shi, Pengfei Ren, Chengjuan Zhang, Zhizhong Wang, Jiuzhou Zhao, Jiawen Zheng, Tingjie Wang, Bing Wei, He Zhang, Rentao Yu, Yihang Shen, Jie Ma, Yongjun Guo |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Annals of Medicine |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/07853890.2025.2489007 |
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