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Mar 15, 2024 (publication date) through May 3, 2026
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Publication Name
World Journal of Gastrointestinal Oncology
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1948-5204
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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
| Zheng HD, Huang QY, Huang QM, Ke XT, Ye K, Lin S, Xu JH. T2-weighted imaging-based radiomic-clinical machine learning model for predicting the differentiation of colorectal adenocarcinoma. World J Gastrointest Oncol 2024; 16(3): 819-832 [PMID: 38577440 DOI: 10.4251/wjgo.v16.i3.819] |
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| For: | Zheng HD, Huang QY, Huang QM, Ke XT, Ye K, Lin S, Xu JH. T2-weighted imaging-based radiomic-clinical machine learning model for predicting the differentiation of colorectal adenocarcinoma. World J Gastrointest Oncol 2024; 16(3): 819-832 [PMID: 38577440 DOI: 10.4251/wjgo.v16.i3.819] |
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| URL: | https://www.wjgnet.com/1948-5204/full/v16/i3/819.htm |
| Number | Citing Articles |
| 1 |
Z. Yuan, J. Ding, Z. Cao, Z. Zhou, X. Chen, W. Wang, J. Zhao, N. Qi. Individualised prediction of HER2 status in colorectal cancer: development and validation of a radiomics prediction model using 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance (18F-FDG PET/MR). Clinical Radiology 2026; 97: 107355 doi: 10.1016/j.crad.2026.107355
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