Yingwei Xue
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Deep learning-based pathomics signature predicts prognosis and treatment response in gastric cancer: a multicenter retrospective study
Abstract The existing TNM staging system provides insufficient prognostic information in gastric cancer (GC) patients. This study aims to establish a pathomics signature of GC (PSGC) that uses deep learning (DL) to directly analyze H&E slides for predicting GC outcomes. We propose a multi-scale graph neural network with gated attention mechanism for multi-instance learning (MS-GMIL) for the construction of PSGC.
Prognostic value of inflammatory indices in papillary gastric carcinom
Back to Journals » Journal of Inflammation Research » Volume 18 Authors Wang Y , Zhu M, Xue Y Received 4 April 2025 Accepted for publication 27 June 2025 Published 15 July 2025 Volume 2025:18 Pages 9243—9259 DOI https://doi.org/10.2147/JIR.S532396 Checked for plagiarism Yes Review by Single anonymous peer review Peer reviewer comments 2 Editor who approved publication: Dr Nadia Andrea Andreani Yufei Wang,1,* Meng Zhu,2,* Yingwei Xue1 1Department of Gastroenterological Surgery, Harbin...
The prealbumin-CD19+ index predicts surgical survival in patients with GC - BMC Cancer
This study included a total of 389 patients, 276 males and 113 females, with a mean age of 59.10 (10.19) years and a mean BMI of 22.98 (3.22) kg/m2. The PALB-CD19+ index was distributed among the patients as follows: 93 individuals scored 0 points, 240 scored 1 point, and 56 scored 2 points.
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