World Journal of Gastroenterology - Baishideng Publishing Group

BPG is committed to discovery and dissemination of knowledge

Cited by in CrossRef

For:	Huang LM, Yang WJ, Huang ZY, Tang CW, Li J. Artificial intelligence technique in detection of early esophageal cancer. World J Gastroenterol 2020; 26(39): 5959-5969 [PMID: 33132647 DOI: 10.3748/wjg.v26.i39.5959]
URL:	https://www.wjgnet.com/1007-9327/full/v26/i39/5959.htm

(322) (274) (0) (0) (0) (13) (7874) (32)

Number	Citing Articles
1	Wenju Du, Nini Rao, Jiahao Yong, Yingchun Wang, Dingcan Hu, Tao Gan, Linlin Zhu, Bing Zeng. Improving the Classification Performance of Esophageal Disease on Small Dataset by Semi-supervised Efficient Contrastive Learning. Journal of Medical Systems 2022; 46(1) doi: 10.1007/s10916-021-01782-z
2	Tian Jin, Yu-Wei Zhou, Pei-Sen Sun, Yue Huang, Jian-Guo Gao, Xi Jin. Unraveling the characteristics of early esophageal neuroendocrine carcinoma using multi-model endoscopy: A retrospective study of serial cases. World Journal of Gastrointestinal Oncology 2025; 17(11): 110715 doi: 10.4251/wjgo.v17.i11.110715 Abstract(102) \| Core Tip(102) \| Full Article(HTML)(355) \| Full Article (PDF)-8368K(79) \| Full Article with Cover (PDF)-8679K(95) \| Full Article (XML)-169K(50) \| Audio-1543K(14) \| Peer-Review Report-295K(47) \| Answering Reviewers-140K(52) \| Times Cited (0) \| Total Visits (743) \| Open
3	Amrit K. Kamboj, Siddharth Agarwal, Prasad G. Iyer. Recent Advances in the Artificial Intelligence–Assisted Detection of Esophageal Neoplasia. Current Treatment Options in Gastroenterology 2021; 19(3) doi: 10.1007/s11938-021-00353-y
4	Olga Brusnic, Adrian Boicean, Cristian Ichim, Paula Anderco, Danusia Onisor. Artificial Intelligence in Gastrointestinal Endoscopy and Hemostatic Decision-Making: Current Evidence, Clinical Implications and Implementation Barriers. Life 2026; 16(5) doi: 10.3390/life16050845
5	Ken Kurisaki, Shinichiro Kobayashi, Taro Akashi, Yasuhiko Nakao, Masayuki Fukumoto, Kaito Tasaki, Tomohiko Adachi, Susumu Eguchi, Kengo Kanetaka. Opportunities and challenges of artificial intelligence-assisted endoscopy and high-quality data for esophageal squamous cell carcinoma. World Journal of Gastrointestinal Oncology 2026; 18(1): 111357 doi: 10.4251/wjgo.v18.i1.111357 Abstract(101) \| Core Tip(118) \| Full Article(HTML)(464) \| Full Article (PDF)-648K(57) \| Full Article with Cover (PDF)-1017K(52) \| Full Article (XML)-239K(60) \| Audio-1996K(29) \| Peer-Review Report-270K(56) \| Answering Reviewers-297K(44) \| Times Cited (1) \| Total Visits (768) \| Open
6	Pierfrancesco Visaggi, Nicola de Bortoli, Brigida Barberio, Vincenzo Savarino, Roberto Oleas, Emma M. Rosi, Santino Marchi, Mentore Ribolsi, Edoardo Savarino. Artificial Intelligence in the Diagnosis of Upper Gastrointestinal Diseases. Journal of Clinical Gastroenterology 2022; 56(1) doi: 10.1097/MCG.0000000000001629
7	Tao Yan, Pak Kin Wong, Ye-Ying Qin. Deep learning for diagnosis of precancerous lesions in upper gastrointestinal endoscopy: A review. World Journal of Gastroenterology 2021; 27(20): 2531-2544 doi: 10.3748/wjg.v27.i20.2531 Abstract(1378) \| Core Tip(1552) \| Full Article(HTML)(6460) \| Full Article (PDF)-6017K(856) \| Full Article (Word)-1085K(389) \| Audio-580K(30) \| Peer-Review Report-508K(309) \| Answering Reviewers-445K(353) \| Times Cited (27) \| Total Visits (9473) \| Open
8	Caroline Gronnier, Denis Collet. New Trends in Esophageal Cancer Management. Cancers 2021; 13(12) doi: 10.3390/cancers13123030
9	Xiang Lin, Zhang Juxiao, Yin Lu, Ji Wenpei. Multimedia Technology and Enhanced Learning. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024; 535 doi: 10.1007/978-3-031-50580-5_9
10	Kyoichi Adachi, Yuri Ebisutani, Yuko Matsubara, Eiko Okimoto, Norihisa Ishimura, Shunji Ishihara. Effectiveness of Artificial Intelligence in Screening Esophagogastroduodenoscopy. Cureus 2025; doi: 10.7759/cureus.79935
11	Pierfrancesco Visaggi, Brigida Barberio, Matteo Ghisa, Mentore Ribolsi, Vincenzo Savarino, Matteo Fassan, Michele Valmasoni, Santino Marchi, Nicola de Bortoli, Edoardo Savarino. Modern Diagnosis of Early Esophageal Cancer: From Blood Biomarkers to Advanced Endoscopy and Artificial Intelligence. Cancers 2021; 13(13) doi: 10.3390/cancers13133162
12	Hong-Tao Qu, Qing Li, Liang Hao, Yan-Jing Ni, Wen-Yu Luan, Zhe Yang, Xiao-Dong Chen, Tong-Tong Zhang, Yan-Dong Miao, Fang Zhang. Esophageal cancer screening, early detection and treatment: Current insights and future directions. World Journal of Gastrointestinal Oncology 2024; 16(4): 1180-1191 doi: 10.4251/wjgo.v16.i4.1180 Abstract(836) \| Core Tip(842) \| Full Article(HTML)(6102) \| Full Article (PDF)-1173K(409) \| Full Article with Cover (PDF)-1403K(454) \| Full Article (XML)-191K(161) \| Audio-1486K(67) \| Peer-Review Report-215K(152) \| Answering Reviewers-142K(141) \| Times Cited (0) \| Total Visits (8138) \| Open
13	Thifhelimbilu Luvhengo, Thulo Molefi, Demetra Demetriou, Rodney Hull, Zodwa Dlamini. Artificial Intelligence and Precision Oncology. 2023; doi: 10.1007/978-3-031-21506-3_3
14	Vikrant Rai, Joe Abdo, Devendra K. Agrawal. Biomarkers for Early Detection, Prognosis, and Therapeutics of Esophageal Cancers. International Journal of Molecular Sciences 2023; 24(4) doi: 10.3390/ijms24043316
15	Jun-Qi Zhang, Jun-Jie Mi, Rong Wang. Application of convolutional neural network-based endoscopic imaging in esophageal cancer or high-grade dysplasia: A systematic review and meta-analysis. World Journal of Gastrointestinal Oncology 2023; 15(11): 1998-2016 doi: 10.4251/wjgo.v15.i11.1998 Abstract(724) \| Core Tip(794) \| Full Article(HTML)(2650) \| Full Article (PDF)-3212K(227) \| Full Article with Cover (PDF)-3503K(223) \| Full Article (Word)-2629K(27) \| Full Article (XML)-231K(159) \| Audio-394K(14) \| Peer-Review Report-206K(150) \| Answering Reviewers-170K(150) \| Times Cited (7) \| Total Visits (4207) \| Open
16	Wei-Chih Liao, Arvind Mukundan, Cleorita Sadiaza, Yu-Ming Tsao, Chien-Wei Huang, Hsiang-Chen Wang. Systematic meta-analysis of computer-aided detection to detect early esophageal cancer using hyperspectral imaging. Biomedical Optics Express 2023; 14(8) doi: 10.1364/BOE.492635
17	Hai Yang, Junyang Cao, Juan Wang. Classification of Esophageal Disease Images Based on Deep Fusion Network with Weight Transfer. 2024 14th International Conference on Software Technology and Engineering (ICSTE) 2024; doi: 10.1109/ICSTE63875.2024.00045
18	Rhiannon McShane, Swati Arya, Alan J. Stewart, Peter D. Caie, Mark Bates. Prognostic features of the tumour microenvironment in oesophageal adenocarcinoma. Biochimica et Biophysica Acta (BBA) - Reviews on Cancer 2021; 1876(2) doi: 10.1016/j.bbcan.2021.188598
19	Jinzhuang Liao, Xiaoying Li, Yu Gan, Shuangze Han, Pengfei Rong, Wei Wang, Wei Li, Li Zhou. Artificial intelligence assists precision medicine in cancer treatment. Frontiers in Oncology 2023; 12 doi: 10.3389/fonc.2022.998222
20	Kai-Yao Yang, Arvind Mukundan, Yu-Ming Tsao, Xian-Hong Shi, Chien-Wei Huang, Hsiang-Chen Wang. Assessment of hyperspectral imaging and CycleGAN-simulated narrowband techniques to detect early esophageal cancer. Scientific Reports 2023; 13(1) doi: 10.1038/s41598-023-47833-y
21	Jinlin Liu, Min Zhang, Min Zhu, Simin Tan, Xuefeng Luo, Jia Liu, Hai Zeng. Comparative analysis of diagnostic techniques and treatment modalities for early-stage esophageal carcinoma: a comprehensive review. Frontiers in Oncology 2025; 15 doi: 10.3389/fonc.2025.1650965
22	Tsung-Jung Tsai, Arvind Mukundan, Yu-Sheng Chi, Yu-Ming Tsao, Yao-Kuang Wang, Tsung-Hsien Chen, I-Chen Wu, Chien-Wei Huang, Hsiang-Chen Wang. Intelligent Identification of Early Esophageal Cancer by Band-Selective Hyperspectral Imaging. Cancers 2022; 14(17) doi: 10.3390/cancers14174292
23	Zong-Yang Li, Ya-Hui Liu, Hong-Qiao Cai. Diagnostic value of real-time computer-aided detection for precancerous lesion during esophagogastroduodenoscopy: A meta-analysis. World Journal of Gastrointestinal Surgery 2025; 17(11): 109991 doi: 10.4240/wjgs.v17.i11.109991 Abstract(120) \| Core Tip(86) \| Full Article(HTML)(324) \| Full Article (PDF)-2493K(99) \| Full Article with Cover (PDF)-2906K(73) \| Full Article (XML)-124K(40) \| Audio-183K(35) \| Peer-Review Report-242K(46) \| Answering Reviewers-222K(92) \| Supplementary Material-47K(28) \| Times Cited (0) \| Total Visits (678) \| Open
24	Si-yan Yan, Xin-yu Fu, Yan Yang, Liu-yi Jia, Jia-wei Liang, Ying-hui Li, Ling-ling Yan, Ying Zhou, Xian-bin Zhou, Shao-wei Li, Xin-li Mao. Artificial intelligence in early screening for esophageal squamous cell carcinoma. Best Practice & Research Clinical Gastroenterology 2025; 75 doi: 10.1016/j.bpg.2025.102004
25	Hongbiao Ma, Longlun Wang, Yilin Chen, Lu Tian. Convolutional neural network-based artificial intelligence for the diagnosis of early esophageal cancer based on endoscopic images. Saudi Journal of Gastroenterology 2022; 28(5) doi: 10.4103/sjg.sjg_178_22
26	Keyu Chen, Zhiyou Yang, Ma Luo, Wei Liu, Yuhang Zhang, Bing Hu, Xianglei Yuan, Wenyu Chen. Esophageal cancer lesion detection with information preservation for multi-modal diagnostic images. Neurocomputing 2025; 654 doi: 10.1016/j.neucom.2025.131317
27	Nripesh Kumar, Ashok Kumar, Ashutosh Pandey, Mithilesh Kumar Sharma, Dhananjay Yadav, Rahul Kumar Singh. Deep Learning Framework for Esophageal Cancer Cell Recognition. 2025 14th International Conference on System Modeling & Advancement in Research Trends (SMART) 2025; doi: 10.1109/SMART66937.2025.11389555
28	Karen E. Villagrana-Bañuelos, Vanessa Alcalá-Rmz, José M. Celaya-Padilla, Jorge I. Galván-Tejada, Hamurabi Gamboa-Rosales, Carlos E. Galván-Tejada. Proceedings of the International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2022). Lecture Notes in Networks and Systems 2023; 594 doi: 10.1007/978-3-031-21333-5_17
29	Himanshu Agrawal, Nikhil Gupta, Himanshu Tanwar, Natasha Panesar. Artificial intelligence in gastrointestinal surgery: A minireview of predictive models and clinical applications. Artificial Intelligence in Gastroenterology 2025; 6(1): 108198 doi: 10.35712/aig.v6.i1.108198 Abstract(796) \| Core Tip(452) \| Full Article(HTML)(1478) \| Full Article (PDF)-713K(174) \| Full Article with Cover (PDF)-923K(223) \| Full Article (XML)-390K(93) \| Audio-2093K(26) \| Peer-Review Report-201K(112) \| Answering Reviewers-248K(158) \| Times Cited (1) \| Total Visits (2708) \| Open
30	Donghong Zhou. Human-Computer Interaction Interface Design in Intelligent Medical System under the Background of Artificial Intelligence. 2022 International Conference on Artificial Intelligence and Autonomous Robot Systems (AIARS) 2022; doi: 10.1109/AIARS57204.2022.00010