For: | Feng B, Ma XH, Wang S, Cai W, Liu XB, Zhao XM. Application of artificial intelligence in preoperative imaging of hepatocellular carcinoma: Current status and future perspectives. World J Gastroenterol 2021; 27(32): 5341-5350 [PMID: 34539136 DOI: 10.3748/wjg.v27.i32.5341] |
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URL: | https://www.wjgnet.com/1007-9327/full/v27/i32/5341.htm |
Number | Citing Articles |
1 |
Liyang Wang, Meilong Wu, Chengzhan Zhu, Rui Li, Shiyun Bao, Shizhong Yang, Jiahong Dong. Ensemble learning based on efficient features combination can predict the outcome of recurrence-free survival in patients with hepatocellular carcinoma within three years after surgery. Frontiers in Oncology 2022; 12 doi: 10.3389/fonc.2022.1019009
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2 |
Thifhelimbilu Luvhengo, Thulo Molefi, Demetra Demetriou, Rodney Hull, Zodwa Dlamini. Artificial Intelligence and Precision Oncology. 2023; : 49 doi: 10.1007/978-3-031-21506-3_3
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3 |
Jin Jin, Ying Jiang, Yu-Lan Zhao, Pin-Tong Huang. Radiomics-based Machine Learning to Predict the Recurrence of Hepatocellular Carcinoma: A Systematic Review and Meta-analysis. Academic Radiology 2024; 31(2): 467 doi: 10.1016/j.acra.2023.09.008
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4 |
Evangelos Chartampilas, Vasileios Rafailidis, Vivian Georgopoulou, Georgios Kalarakis, Adam Hatzidakis, Panos Prassopoulos. Current Imaging Diagnosis of Hepatocellular Carcinoma. Cancers 2022; 14(16): 3997 doi: 10.3390/cancers14163997
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5 |
Jing Yang, Na Lin, Miaomiao Niu, Boshu Yin. Circulating tumor DNA mutation analysis: advances in its application for early diagnosis of hepatocellular carcinoma and therapeutic efficacy monitoring. Aging 2024; 16(14): 11460 doi: 10.18632/aging.205980
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6 |
Chao Lv, Nan He, Jie Jie Yang, Jing Jing Xiao, Yan Zhang, Jun Du, Shi Zuo, Hai Yang Li, Huajian Gu. Prediction of 3-year recurrence rate of hepatocellular carcinoma after resection based on contrast-enhanced CT: a single-centre study. The British Journal of Radiology 2023; 96(1145) doi: 10.1259/bjr.20220702
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7 |
Liuji Sheng, Chongtu Yang, Yidi Chen, Bin Song. Machine Learning Combined with Radiomics Facilitating the Personal Treatment of Malignant Liver Tumors. Biomedicines 2023; 12(1): 58 doi: 10.3390/biomedicines12010058
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8 |
Jianan Chen, Weibin Zhang, Jingwen Bao, Kun Wang, Qiannan Zhao, Yuli Zhu, Yanling Chen. Implications of ultrasound-based deep learning model for preoperatively differentiating combined hepatocellular-cholangiocarcinoma from hepatocellular carcinoma and intrahepatic cholangiocarcinoma. Abdominal Radiology 2023; 49(1): 93 doi: 10.1007/s00261-023-04089-4
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9 |
B. Lakshmipriya, Biju Pottakkat, G. Ramkumar. Deep learning techniques in liver tumour diagnosis using CT and MR imaging - A systematic review. Artificial Intelligence in Medicine 2023; 141: 102557 doi: 10.1016/j.artmed.2023.102557
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10 |
Yang Yan, Zhang Si, Cui Chun, Pen Chao‐qun, Mu Ke, Zhang Dong, Wen Li. Multiphase MRI‐Based Radiomics for Predicting Histological Grade of Hepatocellular Carcinoma. Journal of Magnetic Resonance Imaging 2024; doi: 10.1002/jmri.29289
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11 |
Joseph A. Kavian, Hannah L. Wilkey, Parth A. Patel, Carter J. Boyd. Harvesting the Power of Artificial Intelligence for Surgery: Uses, Implications, and Ethical Considerations. The American Surgeon™ 2023; 89(12): 5102 doi: 10.1177/00031348231175454
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12 |
Mayur Wanjari, Gaurav Mittal, Roshan Prasad. Enhancing neurosurgical interventions for Sturge-Weber syndrome with AI technologies. Neurosurgical Review 2024; 47(1) doi: 10.1007/s10143-024-02887-y
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13 |
Xiaomin Shen, Jinxin Wu, Junwei Su, Zhenyu Yao, Wei Huang, Li Zhang, Yiheng Jiang, Wei Yu, Zhao Li. Revisiting artificial intelligence diagnosis of hepatocellular carcinoma with DIKWH framework. Frontiers in Genetics 2023; 14 doi: 10.3389/fgene.2023.1004481
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14 |
冰洁 李. Deep Learning in the Diagnosis and Treatment of Liver Cancer: Review and Pro-spects. Advances in Clinical Medicine 2023; 13(09): 14103 doi: 10.12677/ACM.2023.1391973
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15 |
Andrew P. Bain, Carla N. Holcomb, Herbert J. Zeh, Ganesh Sankaranarayanan. Artificial intelligence for improving intraoperative surgical care. Global Surgical Education - Journal of the Association for Surgical Education 2024; 3(1) doi: 10.1007/s44186-024-00268-z
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16 |
Ashok Kumar, Anirudh Goyal. Emerging molecules, tools, technology, and future of surgical knife in gastroenterology. World Journal of Gastrointestinal Surgery 2024; 16(4): 988-998 doi: 10.4240/wjgs.v16.i4.988
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17 |
Zerui Zhang, Jianyun Gao, Shu Li, Hao Wang. RMCNet: A Liver Cancer Segmentation Network Based on 3D Multi-Scale Convolution, Attention, and Residual Path. Bioengineering 2024; 11(11): 1073 doi: 10.3390/bioengineering11111073
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18 |
Runzhi Yu, Ziyi Cao, Yiqin Huang, Xuechun Zhang, Jie Chen, Yuchen Li. Establishment and Analysis of a Combined Diagnostic Model of Liver Cancer with Random Forest and Artificial Neural Network. Mathematical Problems in Engineering 2022; 2022: 1 doi: 10.1155/2022/5679837
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