| For: | Li Y, Liu YB, Li XB, Cui XN, Meng DH, Yuan CC, Ye ZX. Deep learning model combined with computed tomography features to preoperatively predicting the risk stratification of gastrointestinal stromal tumors. World J Gastrointest Oncol 2024; 16(12): 4663-4674 [PMID: 39678791 DOI: 10.4251/wjgo.v16.i12.4663] |
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| URL: | https://www.wjgnet.com/1948-5204/full/v16/i12/4663.htm |
| Number | Citing Articles |
| 1 |
Wei Chen, Long-Yu Duan, Kun-Ming Yi, Xiao-Juan Peng, Lian-Qin Kuang. A deep learning-based radiomic nomogram derived from visceral fat for early prediction of gastrointestinal stromal tumor risk grade. Frontiers in Medicine 2026; 13 doi: 10.3389/fmed.2026.1741436
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| 2 |
Mohsen Salimi, Hanieh Mohammadi, Sahar Ghahramani, Maryam Nemati, Anita Ashari, Amirhossein Imani, Mohammad Hossein Imani. Diagnostic accuracy of radiomics in risk stratification of gastrointestinal stromal tumors: A systematic review and meta-analysis. European Journal of Radiology 2025; 190 doi: 10.1016/j.ejrad.2025.112225
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| 3 |
Sihang Guo, Chengze Yu, Jianying Xu, Chuxuan Zhi, Xiuling Gu, Dengfa Yang, Zongyu Xie, Ding Shi, Qinglin Li, Jian Wang. Cross-phase attention-based multi-phase CT deep learning for preoperative risk stratification of gastric gastrointestinal stromal tumors in a multicenter study. European Journal of Radiology 2026; 205 doi: 10.1016/j.ejrad.2026.113237
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