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Cited by in CrossRef
For: Wang YY, Yang WX, Du QJ, Liu ZH, Lu MH, You CG. Construction and evaluation of a liver cancer risk prediction model based on machine learning. World J Gastrointest Oncol 2024; 16(9): 3839-3850 [PMID: 39350987 DOI: 10.4251/wjgo.v16.i9.3839]
URL: https://www.wjgnet.com/1007-9327/full/v16/i9/3839.htm
Number Citing Articles
1
Fu Xu, Yuming Li, Xuanli Zhong, Huafeng Liang, Ruifeng Li, Jun Lyu, Haidi Yang. Development and Validation of a Nomogram Model for Predicting Non-keratinizing Nasopharyngeal Carcinoma by Combining Sex and Three EB Virus AntibodiesCancer Control 2025; 32 doi: 10.1177/10732748251391858
2
Yu-Xuan Xiao, Yi-Xin Zou, Zhuo-Ying Li, Qiu-Ming Shen, Da-Ke Liu, Yu-Ting Tan, Hong-Lan Li, Yong-Bing Xiang. A machine learning approach for a 15-year prediction model of liver cancer incidence: Results from two large Chinese population cohortsAnnals of Epidemiology 2025; 112: 28 doi: 10.1016/j.annepidem.2025.10.015
3
Sugandha Chakraverti, Tejaswi Khanna, Vijay Shukla. Enhanced Pyramid Scene Parsing Network for Segmentation and Deep Dilated Residual CNN-based Sparrow Search Optimization for Efficient Liver Tumor DetectionJournal of Multiscale Modelling 2025; 16(03) doi: 10.1142/S1756973725500088
4
Anran Liu, Jiang Zhang, Tong Li, Danyang Zheng, Yihong Ling, Lianghe Lu, Yuanpeng Zhang, Jing Cai. Explainable attention-enhanced heuristic paradigm for multi-view prognostic risk score development in hepatocellular carcinomaHepatology International 2025; 19(4): 866 doi: 10.1007/s12072-025-10793-8