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Cited by in CrossRef
For: Wei X, Yan XJ, Guo YY, Zhang J, Wang GR, Fayyaz A, Yu J. Machine learning-based gray-level co-occurrence matrix signature for predicting lymph node metastasis in undifferentiated-type early gastric cancer. World J Gastroenterol 2022; 28(36): 5338-5350 [PMID: 36185632 DOI: 10.3748/wjg.v28.i36.5338]
URL: https://www.wjgnet.com/1007-9327/full/v28/i36/5338.htm
Number Citing Articles
1
You-Na Sung. Interpretable deep learning model to predict lymph node metastasis in early gastric cancer using whole slide imagesAmerican Journal of Cancer Research 2024; 14(7): 3513 doi: 10.62347/RJBH6076
2
Wei-Ling Zhang, Jing Sun, Rong-Fang Huang, Yi Zeng, Shu Chen, Xiao-Peng Wang, You-Ping Xiao, Zai-Sheng Ye, Chun-Su Zhu, Yun-Bin Chen, Jin-Hu Chen. Whole-volume histogram analysis of spectral-computed tomography iodine maps characterizes HER2 expression in gastric cancerWorld Journal of Gastroenterology 2024; 30(38): 4211-4220 doi: 10.3748/wjg.v30.i38.4211
3
Marianne Linley L. Sy-Janairo, Jose Isagani B. Janairo. Non-endoscopic Applications of Machine Learning in Gastric Cancer: A Systematic ReviewJournal of Gastrointestinal Cancer 2024; 55(1): 47 doi: 10.1007/s12029-023-00960-1
4
Rafael Vinícius Da Silveira, Thamires Naela Cardoso Magalhães, Marcio Luiz Figueredo Balthazar, Gabriela Castellano. Differences between Alzheimer’s disease and mild cognitive impairment using brain networks from magnetic resonance texture analysisExperimental Brain Research 2024; 242(8): 1947 doi: 10.1007/s00221-024-06871-2
5
Atefeh Talebi, Carlos A. Celis-Morales, Nasrin Borumandnia, Somayeh Abbasi, Mohamad Amin Pourhoseingholi, Abolfazl Akbari, Javad Yousefi. Predicting metastasis in gastric cancer patients: machine learning-based approachesScientific Reports 2023; 13(1) doi: 10.1038/s41598-023-31272-w