For: | Ma ZH, Wang YP, Zheng WH, Ma J, Bai X, Zhang Y, Wang YH, Chi D, Fu XB, Hua XD. Prognostic factors and therapeutic effects of different treatment modalities for colorectal cancer liver metastases. World J Gastrointest Oncol 2020; 12(10): 1177-1194 [PMID: PMC7579728 DOI: 10.4251/wjgo.v12.i10.1177] |
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URL: | https://www.wjgnet.com/1948-9366/full/v12/i10/1177.htm |
Number | Citing Articles |
1 |
Qunzhe Ding, Chenyang Li, Chendong Wang, Qunzhe Ding. Construction and interpretation of weight-balanced enhanced machine learning models for predicting liver metastasis risk in colorectal cancer patients. Discover Oncology 2025; 16(1) doi: 10.1007/s12672-025-01871-2
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2 |
Vincenza Granata, Roberta Fusco, Federica De Muzio, Carmen Cutolo, Sergio Venanzio Setola, Federica dell’ Aversana, Alessandro Ottaiano, Antonio Avallone, Guglielmo Nasti, Francesca Grassi, Vincenzo Pilone, Vittorio Miele, Luca Brunese, Francesco Izzo, Antonella Petrillo. Contrast MR-Based Radiomics and Machine Learning Analysis to Assess Clinical Outcomes following Liver Resection in Colorectal Liver Metastases: A Preliminary Study. Cancers 2022; 14(5): 1110 doi: 10.3390/cancers14051110
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3 |
Hongmei Wang, Xuefeng Shan, Min Zhang, Kun Qian, Zhengze Shen, Weiying Zhou. Nomograms for predicting overall survival in colorectal cancer patients with metastasis to the liver, lung, bone, and brain. Cancer Causes & Control 2023; 34(12): 1059 doi: 10.1007/s10552-023-01744-5
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