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Cited by in CrossRef
For: Wei ZY, Zhang Z, Zhao DL, Zhao WM, Meng YG. Magnetic resonance imaging-based radiomics model for preoperative assessment of risk stratification in endometrial cancer. World J Clin Cases 2024; 12(26): 5908-5921 [PMID: 39286374 DOI: 10.12998/wjcc.v12.i26.5908]
URL: https://www.wjgnet.com/2307-8960/full/v12/i26/5908.htm
Number Citing Articles
1
Ridhima Suthar, Rati Yadav, Pallavi Kumari, Neelesh Kumar Mehra. Nanotechnology in gynaecological cancers: Biomedical perspectives on lipid-based drug delivery systems for targeted therapyInternational Journal of Pharmaceutics 2026; 687 doi: 10.1016/j.ijpharm.2025.126402
2
YUFENG GONG, YING CUI, CHUNJING MA, SHIHUI MIN, PENGKAI WANG, LI MA. DEEP LEARNING-BASED MAGNETIC RESONANCE IMAGING ARTIFICIAL INTELLIGENCE CLASSIFICATION TECHNOLOGY IN THE DIAGNOSIS OF ENDOMETRIAL CANCERJournal of Mechanics in Medicine and Biology 2026;  doi: 10.1142/S0219519426500533
3
Xiaoli Peng, Qisen Zhu, Lu Zhao, Ruyun Li, Ling Tu, Jiao Chen, Guocheng Du, Maochun Zhang. Prediction of cervical stromal invasion using ultrasound radiomics: from conventional ultrasound to intelligent diagnosisFrontiers in Oncology 2026; 16 doi: 10.3389/fonc.2026.1817583