Development of a tongue image-based machine learning tool for the diagnosis of gastric cancer: a prospective multicentre clinical cohort study.
Yuan L, Yang L, Zhang S, Xu Z, Qin J, Shi Y, Yu P, Wang Y, Bao Z, Xia Y, Sun J, He W, Chen T, Chen X, Hu C, Zhang Y, Dong C, Zhao P, Wang Y, Jiang N, Lv B, Xue Y, Jiao B, Gao H, Chai K, Li J, Wang H, Wang X, Guan X, Liu X, Zhao G, Zheng Z, Yan J, Yu H, Chen L, Ye Z, You H, Bao Y, Cheng X, Zhao P, Wang L, Zeng W, Tian Y, Chen M, You Y, Yuan G, Ruan H, Gao X, Xu J, Xu H, Du L, Zhang S, Fu H, Cheng X.
Yuan L, et al. Among authors: chen m.
EClinicalMedicine. 2023 Feb 6;57:101834. doi: 10.1016/j.eclinm.2023.101834. eCollection 2023 Mar.
EClinicalMedicine. 2023.
PMID: 36825238
Free PMC article.
METHODS: From May 2020 to January 2021, we simultaneously collected tongue images and tongue coating samples from 328 patients with GC (all newly diagnosed with GC) and 304 non-gastric cancer (NGC) participants in China, and 16 S rDNA was used to characterize the microbiom …
METHODS: From May 2020 to January 2021, we simultaneously collected tongue images and tongue coating samples from 328 patients with GC (all …