| For: | Zhou LQ, Wang JY, Yu SY, Wu GG, Wei Q, Deng YB, Wu XL, Cui XW, Dietrich CF. Artificial intelligence in medical imaging of the liver. World J Gastroenterol 2019; 25(6): 672-682 [PMID: 30783371 DOI: 10.3748/wjg.v25.i6.672] |
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| URL: | https://www.wjgnet.com/1007-9327/full/v25/i6/672.htm |
| Number | Citing Articles |
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| 23 |
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Shuli Tang, Tiantian Fan, Xinxin Wang, Can Yu, Chunhui Zhang, Yang Zhou. Cancer Immunotherapy and Medical Imaging Research Trends from 2003 to 2023: A Bibliometric Analysis. Journal of Multidisciplinary Healthcare 2024; doi: 10.2147/JMDH.S457367
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Ashok Kamalanathan, Babu Muthu, Patheri Kuniyil Kaleena. Marvels of Artificial and Computational Intelligence in Life Sciences. 2023; doi: 10.2174/9789815136807123010009
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| 31 |
Lanping Wu, Bin Dong, Xiaoqing Liu, Wenjing Hong, Lijun Chen, Kunlun Gao, Qiuyang Sheng, Yizhou Yu, Liebin Zhao, Yuqi Zhang. Standard Echocardiographic View Recognition in Diagnosis of Congenital Heart Defects in Children Using Deep Learning Based on Knowledge Distillation. Frontiers in Pediatrics 2022; 9 doi: 10.3389/fped.2021.770182
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| 32 |
Soo Yun Choi, Sunggyun Park, Minchul Kim, Jongchan Park, Ye Ra Choi, Kwang Nam Jin. Evaluation of a deep learning-based computer-aided detection algorithm on chest radiographs. Medicine 2021; 100(16) doi: 10.1097/MD.0000000000025663
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Zhongyu Yuan, Jiaxuan Peng, Zhenyu Shu, Xue Qin, Jianguo Zhong. Interpretable multitemporal liver function indicator model for prediction and risk factor analysis of drug induced liver injury. Scientific Reports 2024; 14(1) doi: 10.1038/s41598-024-66952-8
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Chiyu Cai, Liancai Wang, Lianyuan Tao, Hengli Zhu, Yongnian Ren, Deyu Li, Dongxiao Li. Imaging‐Based Prediction of Ki‐67 Expression in Hepatocellular Carcinoma: A Retrospective Study. Cancer Medicine 2025; 14(4) doi: 10.1002/cam4.70562
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| 38 |
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Kamran Sattar Awaisi, Qiang Ye, Srinivas Sampalli. A Survey of Industrial AIoT: Opportunities, Challenges, and Directions. IEEE Access 2024; 12 doi: 10.1109/ACCESS.2024.3426279
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Brian J. Thomsen, Michael Ward, Jin Y. Heo, Elizabeth Huynh, Marc A. Ledesma, Jason A. Fuerst, Arathi Vinayak. Computed tomography scan accuracy for the prediction of lobe and division of liver tumors by four board‐certified radiologists. Veterinary Surgery 2024; 53(7) doi: 10.1111/vsu.14142
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Shanmugapriya Survarachakan, Pravda Jith Ray Prasad, Rabia Naseem, Javier Pérez de Frutos, Rahul Prasanna Kumar, Thomas Langø, Faouzi Alaya Cheikh, Ole Jakob Elle, Frank Lindseth. Deep learning for image-based liver analysis — A comprehensive review focusing on malignant lesions. Artificial Intelligence in Medicine 2022; 130 doi: 10.1016/j.artmed.2022.102331
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Pranav Ajmera, Ryan Dillard, Timothy Kline, Andrew Missert, Panagiotis Korfiatis, Ashish Khandelwal. FDA-approved artificial intelligence products in abdominal imaging: A comprehensive review. Current Problems in Diagnostic Radiology 2026; 55(2) doi: 10.1067/j.cpradiol.2025.04.011
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Keith Feldman, Justin Baraboo, Deeyendal Dinakarpandian, Sherwin S. Chan. Machine Learning Algorithm Improves the Prediction of Transplant Hepatic Artery Stenosis or Occlusion. Ultrasound Quarterly 2022; doi: 10.1097/RUQ.0000000000000624
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Chi-Chih Wang, Yu-Ching Chiu, Wei-Liang Chen, Tzu-Wei Yang, Ming-Chang Tsai, Ming-Hseng Tseng. A Deep Learning Model for Classification of Endoscopic Gastroesophageal Reflux Disease. International Journal of Environmental Research and Public Health 2021; 18(5) doi: 10.3390/ijerph18052428
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