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An artificial intelligence model to predict survival and chemotherapy benefits for gastric cancer patients after gastrectomy development and validation in international multicenter cohorts.
Li X, Zhai Z, Ding W, Chen L, Zhao Y, Xiong W, Zhang Y, Lin D, Chen Z, Wang W, Gao Y, Cai S, Yu J, Zhang X, Liu H, Li G, Chen T. Li X, et al. Among authors: wang w. Int J Surg. 2022 Sep;105:106889. doi: 10.1016/j.ijsu.2022.106889. Epub 2022 Sep 6. Int J Surg. 2022. PMID: 36084807 Free article.
Predicting peritoneal recurrence and disease-free survival from CT images in gastric cancer with multitask deep learning: a retrospective study.
Jiang Y, Zhang Z, Yuan Q, Wang W, Wang H, Li T, Huang W, Xie J, Chen C, Sun Z, Yu J, Xu Y, Poultsides GA, Xing L, Zhou Z, Li G, Li R. Jiang Y, et al. Among authors: wang h, wang w. Lancet Digit Health. 2022 May;4(5):e340-e350. doi: 10.1016/S2589-7500(22)00040-1. Lancet Digit Health. 2022. PMID: 35461691 Free article.
Radiomics signature based on computed tomography images for the preoperative prediction of lymph node metastasis at individual stations in gastric cancer: A multicenter study.
Sun Z, Jiang Y, Chen C, Zheng H, Huang W, Xu B, Tang W, Yuan Q, Zhou K, Liang X, Chen H, Han Z, Feng H, Yu S, Hu Y, Yu J, Zhou Z, Wang W, Xu Y, Li G. Sun Z, et al. Among authors: wang w. Radiother Oncol. 2021 Dec;165:179-190. doi: 10.1016/j.radonc.2021.11.003. Epub 2021 Nov 11. Radiother Oncol. 2021. PMID: 34774652
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