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Cited by in CrossRef
For: Liu MC, Cheng YY, Lin SC, Lin CH, Chuang CY, Chen WH, Liao CH, Hsieh CH, Hsieh MF, Liu YJ. Machine learning survival prediction in esophageal cancer using radiomics and body composition from pretreatment and follow-up T12-level computed tomography. World J Gastrointest Oncol 2025; 17(12): 112873 [PMID: 41480227 DOI: 10.4251/wjgo.v17.i12.112873]
URL: https://www.wjgnet.com/1948-5204/full/v17/i12/112873.htm
Number Citing Articles
1
Sivan Sathish, Ankita Jain, Kratee Sharma, Karthika B. Artificial intelligence in quantitative imaging of esophageal cancer: A review on radiomics, sarcopenia, and survival modelingWorld Journal of Gastrointestinal Oncology 2026; 18(7): 119986 doi: 10.4251/wjgo.v18.i7.119986
2
Fangyuan Long, Hongru Zhang, Shungeng Zhang, Zongfu Dong, Xupeng Huang, Ronghang Hu. Machine learning applications in the detection and treatment of esophageal cancerDiscover Oncology 2026; 17(1) doi: 10.1007/s12672-026-05477-0