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Cited by in CrossRef
For: Qian GX, Xu ZL, Li YH, Lu JL, Bu XY, Wei MT, Jia WD. Computed tomography-based radiomics to predict early recurrence of hepatocellular carcinoma post-hepatectomy in patients background on cirrhosis. World J Gastroenterol 2024; 30(15): 2128-2142 [PMID: 38681988 DOI: 10.3748/wjg.v30.i15.2128]
URL: https://www.wjgnet.com/2220-3249/full/v30/i15/2128.htm
Number Citing Articles
1
Liyang Yang, Disi Liu, Shanshan Yang, Jiewen Chen, Ge Wen. Preoperative Prediction of TACE Refractoriness in Hepatocellular Carcinoma Using CT-Based Radiomics ModelJournal of Hepatocellular Carcinoma 2026;  doi: 10.2147/JHC.S587246
2
Bappah Suleiman Yahaya, Noor Diyana Osman, Noor Khairiah A. Karim, Gokula Kumar Appalanaido, Iza Sazanita Isa, Nasibah Mohamad. Proceedings of IUPESM World Congress on Medical Physics and Biomedical Engineering XXVIIIFMBE Proceedings 2026; 139 doi: 10.1007/978-3-032-20287-1_61
3
Abdullah K. Malik, Daniel Geh, Thomas R. Jeffry Evans, Pierce K. H. Chow, Derek A. Mann, Steven A. White. Improving surgical treatments for hepatocellular carcinomaNature Reviews Gastroenterology & Hepatology 2026; 23(3) doi: 10.1038/s41575-025-01143-y
4
Bappah Suleiman Yahaya, Noor Diyana Osman, Noor Khairiah A. Karim, Gokula Kumar Appalanaido, Iza Sazanita Isa. Radiomics and deep learning characterisation of liver malignancies in CT images – A systematic reviewComputers in Biology and Medicine 2025; 194 doi: 10.1016/j.compbiomed.2025.110491
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) doi: 10.3390/biomedicines13051237
6
Rundong Wang, Yujie Li, Xiaojian Zhang, Liang Yan, Ziling Xu, Zihan Chen, Haibo Wu, Weidong Jia. Multi-phase CT-based intratumoral and peritumoral radiomics for predicting tertiary lymphoid structures of hepatocellular carcinoma: a multi-center retrospective cohort studyEuropean Journal of Surgical Oncology 2026; 52(2) doi: 10.1016/j.ejso.2025.111341
7
Yong-hai Li, Gui-xiang Qian, Yu Zhu, Xue-di Lei, Lei Tang, Xiang-yi Bu, Ming-tong Wei, Wei-dong Jia. An Integrated Model Combined Conventional Radiomics and Deep Learning Features to Predict Early Recurrence of Hepatocellular Carcinoma Eligible for Curative Ablation: A Multicenter Cohort StudyJournal of Computer Assisted Tomography 2025; 49(6) doi: 10.1097/RCT.0000000000001764
8
Yong-Hai Li, Gui-Xiang Qian, Ling Yao, Xue-Di Lei, Yu Zhu, Lei Tang, Zi-Ling Xu, Xiang-Yi Bu, Ming-Tong Wei, Jian-Lin Lu, Wei-Dong Jia. Preoperative model for predicting early recurrence in hepatocellular carcinoma patients using radiomics and deep learning: A multicenter studyWorld Journal of Gastrointestinal Oncology 2025; 17(6): 106608 doi: 10.4251/wjgo.v17.i6.106608
9
Radiodiagnosis in the Era of AIAdvances in Computational Intelligence and Robotics 2025;  doi: 10.4018/979-8-3373-0903-3.ch003
10
K. Sweta, W. Dkhar, R. Kadavigere, A. Pradhan, K. Nayak, S. Sukumar, N.A. Barnes. Diagnostic accuracy of computed tomography (CT)-based radiomics and artificial intelligence (AI) models in hepatocellular carcinoma: a systematic review and meta-analysisClinical Radiology 2025; 89 doi: 10.1016/j.crad.2025.107042
11
Ganji Purnachandra Nagaraju, Tatekalva Sandhya, Mundla Srilatha, Swapna Priya Ganji, Madhu Sudhana Saddala, Bassel F. El-Rayes. Artificial intelligence in gastrointestinal cancers: Diagnostic, prognostic, and surgical strategiesCancer Letters 2025; 612 doi: 10.1016/j.canlet.2025.217461
12
Seoung Hoon Kim. Letter to the Editor: Methodological considerations for computed tomography-based radiomics models predicting early recurrence in hepatocellular carcinomaWorld Journal of Gastroenterology 2026; 32(31): 117415 doi: 10.3748/wjg.117415
13
Manil D Chouhan, Kate McLean, James A Thomas, Jason Dowling. Artificial intelligence prognostication of liver disease using imagingBritish Journal of Radiology 2026; 99(1182) doi: 10.1093/bjr/tqag070
14
Naoshi Nishida. Advancements in Artificial Intelligence-Enhanced Imaging Diagnostics for the Management of Liver Disease—Applications and Challenges in Personalized CareBioengineering 2024; 11(12) doi: 10.3390/bioengineering11121243