World Journal of Gastrointestinal Oncology - Baishideng Publishing Group

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Cited by in CrossRef

For:	Yang RH, Fan WX, Zhong Y, Lin ZP, Chen JP, Jiang GH, Dai HY. Predicting esophageal cancer response to neoadjuvant therapy with magnetic resonance imaging radiomics. World J Gastrointest Oncol 2025; 17(10): 110671 [PMID: 41114118 DOI: 10.4251/wjgo.v17.i10.110671]
URL:	https://www.wjgnet.com/1948-5204/full/v17/i10/110671.htm

Number	Citing Articles
1	Fangyuan Long, Hongru Zhang, Shungeng Zhang, Zongfu Dong, Xupeng Huang, Ronghang Hu. Machine learning applications in the detection and treatment of esophageal cancer. Discover Oncology 2026; 17(1) doi: 10.1007/s12672-026-05477-0
2	Zong-Xian Zhao. Radiomics-based model for predicting neoadjuvant therapy response in esophageal cancer: Limitations and suggestions. World Journal of Gastrointestinal Oncology 2026; 18(2): 114981 doi: 10.4251/wjgo.v18.i2.114981 Abstract(67) \| Core Tip(72) \| Full Article(HTML)(240) \| Full Article (PDF)-437K(81) \| Full Article with Cover (PDF)-770K(241) \| Full Article (XML)-109K(38) \| Audio-1857K(20) \| Peer-Review Report-248K(46) \| Answering Reviewers-185K(51) \| Times Cited (1) \| Total Visits (651) \| Open
3	Sivan Sathish, Ankita Jain, Kratee Sharma, Karthika B. Artificial intelligence in quantitative imaging of esophageal cancer: A review on radiomics, sarcopenia, and survival modeling. World Journal of Gastrointestinal Oncology 2026; 18(7): 119986 doi: 10.4251/wjgo.v18.i7.119986 Abstract(20) \| Core Tip(17) \| Full Article(HTML)(96) \| Full Article (PDF)-1505K(19) \| Full Article with Cover (PDF)-1861K(10) \| Full Article (XML)-141K(10) \| Audio-348K(1) \| Peer-Review Report-293K(11) \| Answering Reviewers-91K(12) \| Times Cited (0) \| Total Visits (180) \| Open