| For: | Yan H, Yu TN. Radiomics-clinical nomogram for response to chemotherapy in synchronous liver metastasis of colorectal cancer: Good, but not good enough. World J Gastroenterol 2022; 28(9): 973-975 [PMID: 35317054 DOI: 10.3748/wjg.v28.i9.973] |
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| URL: | https://www.wjgnet.com/1007-9327/full/v28/i9/973.htm |
| Number | Citing Articles |
| 1 |
Junchuan Li, Li Liu, Xiaoqiong Zhong, Runxin Yang, Wenfeng Wang, Lian Yin, Dong Li, Hua Liu. Comprehensive machine learning analysis of a radiomics-based model for predicting microsatellite instability in right Colon Cancer. Frontiers in Oncology 2026; 16 doi: 10.3389/fonc.2026.1759980
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| 2 |
Vincenza Granata, Roberta Fusco, Maria Chiara Brunese, Gerardo Ferrara, Fabiana Tatangelo, Alessandro Ottaiano, Antonio Avallone, Vittorio Miele, Nicola Normanno, Francesco Izzo, Antonella Petrillo. Machine Learning and Radiomics Analysis for Tumor Budding Prediction in Colorectal Liver Metastases Magnetic Resonance Imaging Assessment. Diagnostics 2024; 14(2): 152 doi: 10.3390/diagnostics14020152
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| 3 |
Reza Elahi, Parsa Karami, Mohammadreza Amjadzadeh, Mahdis Nazari. Radiomics-based artificial intelligence (AI) models in colorectal cancer (CRC) diagnosis, metastasis detection, prognosis, and treatment response prediction. Abdominal Radiology 2025; 51(4): 2153 doi: 10.1007/s00261-025-05201-6
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