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Cited by in CrossRef
For: Deng PZ, Zhao BG, Huang XH, Xu TF, Chen ZJ, Wei QF, Liu XY, Guo YQ, Yuan SG, Liao WJ. Preoperative contrast-enhanced computed tomography-based radiomics model for overall survival prediction in hepatocellular carcinoma. World J Gastroenterol 2022; 28(31): 4376-4389 [PMID: 36159012 DOI: 10.3748/wjg.v28.i31.4376]
URL: https://www.wjgnet.com/1007-9327/full/v28/i31/4376.htm
Number Citing Articles
1
Shili Zhou, Pinjing Hui. Predictive value of contrast-enhanced carotid ultrasound features for stroke risk: a systematic review and meta-analysisFrontiers in Neurology 2025; 16 doi: 10.3389/fneur.2025.1487850
2
Minh Huu Nhat Le, Hien Quang Kha, Nghia Minh Tran, Phat Ky Nguyen, Han H. Huynh, Phat Kim Huynh, Han Lam, Nguyen Quoc Khanh Le. Radiomics in liver research: A paradigm shift in disease detection and stagingEuropean Journal of Radiology Artificial Intelligence 2025; 2: 100016 doi: 10.1016/j.ejrai.2025.100016
3
Zeng Haiyong, Li Wencai, Zhou Yunxiang, Xia Shaohuai, Zeng Kailiang, Xu Ke, Qiu Wenjie, Zhu Gang, Chen Jiansheng, Deng Yifan, Qin Zhongzong, Li Huanpeng, Luo Honghai. Construction of a Nomogram Prediction Model for Prognosis in Patients with Large Artery Occlusion-Acute Ischemic StrokeWorld Neurosurgery 2023; 172: e39 doi: 10.1016/j.wneu.2022.11.117
4
Liuji Sheng, Chongtu Yang, Yidi Chen, Bin Song. Machine Learning Combined with Radiomics Facilitating the Personal Treatment of Malignant Liver TumorsBiomedicines 2023; 12(1): 58 doi: 10.3390/biomedicines12010058
5
Peng Zhang, Yue Shi, Maoting Zhou, Qi Mao, Yunyun Tao, Lin Yang, Xiaoming Zhang. A CECT-Based Radiomics Nomogram Predicts the Overall Survival of Patients with Hepatocellular Carcinoma After Surgical ResectionBiomedicines 2025; 13(5): 1237 doi: 10.3390/biomedicines13051237
6
Yongfei Zheng, Xu Chen, He Zhang, Xiaoxiang Ning, Yichuan Mao, Hailan Zheng, Guojiao Dai, Binghui Liu, Guohua Zhang, Danjiang Huang. Multiparametric MRI-based radiomics nomogram for the preoperative prediction of lymph node metastasis in rectal cancer: A two-center studyEuropean Journal of Radiology 2024; 178: 111591 doi: 10.1016/j.ejrad.2024.111591
7
Defne Cigdem Koc, Ion Bogdan Mănescu, Măriuca Mănescu, Minodora Dobreanu. A Review of the Prognostic Significance of Neutrophil-to-Lymphocyte Ratio in Nonhematologic MalignanciesDiagnostics 2024; 14(18): 2057 doi: 10.3390/diagnostics14182057
8
Rajalaxmi R R, Gothai E, Saraa R, Nikitha S. Feature Selection Using Binary Grey Wolf Optimization for Survival Prediction of Hepatocellular Carcinoma2024 International Conference on IoT Based Control Networks and Intelligent Systems (ICICNIS) 2024; : 1601 doi: 10.1109/ICICNIS64247.2024.10823297
9
Azita Shahraki-Mohammadi, Ali Aliabadi, Afsaneh Karimi. Clinical Application of Artificial Intelligence in Cancer Treatment: A Systematic Literature ReviewHealth Scope 2025; 14(2) doi: 10.5812/healthscope-158492
10
Yen-Wei Chu, Chi-Chang Chang. Editorial: Using physical & genomics markers for smart therapy via expert systems with computer learningFrontiers in Genetics 2023; 14 doi: 10.3389/fgene.2023.1336399
11
Lidi Ma, Congrui Li, Haixia Li, Cheng Zhang, Kan Deng, Weijing Zhang, Chuanmiao Xie. Deep learning model based on contrast-enhanced MRI for predicting post-surgical survival in patients with hepatocellular carcinomaHeliyon 2024; 10(11): e31451 doi: 10.1016/j.heliyon.2024.e31451
12
Ting Dai, Qian-Biao Gu, Ying-Jie Peng, Chuan-Lin Yu, Peng Liu, Ya-Qiong He. Preoperative Noninvasive Prediction of Recurrence-Free Survival in Hepatocellular Carcinoma Using CT-Based Radiomics ModelJournal of Hepatocellular Carcinoma 2024; : 2211 doi: 10.2147/JHC.S493044