| For: | Cai LQ, Yang DQ, Wang RJ, Huang H, Shi YX. Establishing and clinically validating a machine learning model for predicting unplanned reoperation risk in colorectal cancer. World J Gastroenterol 2024; 30(23): 2991-3004 [PMID: 38946868 DOI: 10.3748/wjg.v30.i23.2991] |
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| URL: | https://www.wjgnet.com/1007-9327/full/v30/i23/2991.htm |
| Number | Citing Articles |
| 1 |
Feifan Song, Shiqiang Su, Xueqiao Zhang, Yunpeng Cao, Xiongjie Cui, Lili Zhang, Chao Li, Shen Li. Association between the red cell distribution width-to-albumin ratio and recurrence-free survival and overall survival in patients with non-muscle-invasive bladder cancer: a retrospective cohort study. Frontiers in Oncology 2026; 15 doi: 10.3389/fonc.2025.1710047
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| 2 |
Mikiyas Amare Getu, Tesfaye Amare, Kefeng Li, Anam Mehmood, Yonas Fissha Adem, Pablo Santos, Hu Yan. Machine learning and deep learning models for predicting colorectal cancer metastases: A comprehensive review. European Journal of Radiology Open 2026; 16: 100747 doi: 10.1016/j.ejro.2026.100747
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| 3 |
Hajra Asad, Owais Ahmad, Enjizab Fatima. Letter to editor: Optimized machine learning model for predicting unplanned reoperation after rectal cancer anterior resection. European Journal of Surgical Oncology 2025; 51(1): 109371 doi: 10.1016/j.ejso.2024.109371
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| 4 |
Yongpeng Ouyang, Ding Li, Binsong Xia, Kunjian Xia. The clinical application value of body composition in predicting the prognosis of rectal cancer. International Journal of Clinical Oncology 2026; 31(5): 915 doi: 10.1007/s10147-026-03015-0
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| 5 |
Ionut Negoi. Personalized surveillance in colorectal cancer: Integrating circulating tumor DNA and artificial intelligence into post-treatment follow-up. World Journal of Gastroenterology 2025; 31(18): 106670 doi: 10.3748/wjg.v31.i18.106670
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| 6 |
Mengmeng Zhang, Xi Wu, Dongsheng Wu, Qingwei Jiang, Yunlu Feng, Qiang Wang, Shengyu Zhang, Aiming Yang. Long-term prognosis and risk factors associated with 30-day unplanned repeated ERCP in patients with common bile duct stones. Therapeutic Advances in Gastroenterology 2025; 18 doi: 10.1177/17562848251342342
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| 7 |
Yang Su, Yanqi Li, Wangshuo Yang, Xuelai Luo, Lisheng Chen. Optimized machine learning model for predicting unplanned reoperation after rectal cancer anterior resection. European Journal of Surgical Oncology 2024; 50(12): 108703 doi: 10.1016/j.ejso.2024.108703
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| 8 |
Xiaobo Ye, Hui Li, Xi Zhang, Jiahao Lian, Yicong Dong, Yutao Ren, Huanfa Li, Yong Liu, Changwang Du, Hao Wu, Qiang Meng, Hua Zhang. Development and validation of an interpretable prediction model for the risk of unplanned reoperation in patients underwent intracranial tumor surgery. Scientific Reports 2026; doi: 10.1038/s41598-026-43594-6
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| 9 |
永煜 杨. Progress in Machine Learning Applications for Colorectal Cancer. Journal of Clinical Personalized Medicine 2025; 4(06): 56 doi: 10.12677/jcpm.2025.46477
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