World Journal of Gastroenterology - Baishideng Publishing Group

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For:	Li B, Cai SL, Tan WM, Li JC, Yalikong A, Feng XS, Yu HH, Lu PX, Feng Z, Yao LQ, Zhou PH, Yan B, Zhong YS. Comparative study on artificial intelligence systems for detecting early esophageal squamous cell carcinoma between narrow-band and white-light imaging. World J Gastroenterol 2021; 27(3): 281-293 [PMID: 33519142 DOI: 10.3748/wjg.v27.i3.281]
URL:	https://www.wjgnet.com/1007-9327/full/v27/i3/281.htm

(309) (297) (0) (0) (0) (16) (7757) (46)

Number	Citing Articles
1	浩王. Research Progress on Artificial Intelligence-Assisted Endoscopic Identification of Esophageal Cancer. Advances in Clinical Medicine 2024; 14(09) doi: 10.12677/acm.2024.1492521
2	Eyad Gadour, Bodour Raheem, Antonio Facciorusso. A critical review of technical progress, clinical heterogeneity, and implementation challenges of artificial intelligence in digestive endoscopy. Expert Review of Gastroenterology & Hepatology 2026; 20(4) doi: 10.1080/17474124.2026.2646299
3	Kotaro Waki, Katsuya Nagaoka, Keishi Okubo, Masato Kiyama, Ryosuke Gushima, Kento Ohno, Munenori Honda, Akira Yamasaki, Kenshi Matsuno, Yoki Furuta, Hideaki Miyamoto, Hideaki Naoe, Motoki Amagasaki, Yasuhito Tanaka. Optimizing AI models to predict esophageal squamous cell carcinoma risk by incorporating small datasets of soft palate images. Scientific Reports 2025; 15(1) doi: 10.1038/s41598-025-86829-8
4	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
5	Sayaka Nagao, Yasuhiro Tani, Junichi Shibata, Yosuke Tsuji, Tomohiro Tada, Ryu Ishihara, Mitsuhiro Fujishiro. Implementation of artificial intelligence in upper gastrointestinal endoscopy. DEN Open 2022; 2(1) doi: 10.1002/deo2.72
6	Qian-Qian Meng, Ye Gao, Han Lin, Tian-Jiao Wang, Yan-Rong Zhang, Jian Feng, Zhao-Shen Li, Lei Xin, Luo-Wei Wang. Application of an artificial intelligence system for endoscopic diagnosis of superficial esophageal squamous cell carcinoma. World Journal of Gastroenterology 2022; 28(37): 5483-5493 doi: 10.3748/wjg.v28.i37.5483 Abstract(1138) \| Core Tip(939) \| Full Article(HTML)(3347) \| Full Article (PDF)-3038K(473) \| Full Article (Word)-1880K(91) \| Audio-11356K(13) \| Peer-Review Report-245K(176) \| Answering Reviewers-75K(191) \| Times Cited (28) \| Total Visits (5385) \| Open
7	Piyush Nathani, Prateek Sharma. Role of Artificial Intelligence in the Detection and Management of Premalignant and Malignant Lesions of the Esophagus and Stomach. Gastrointestinal Endoscopy Clinics of North America 2025; 35(2) doi: 10.1016/j.giec.2024.10.003
8	Xia Yin, Miao Meng. Comparison of the diagnostic value of white light endoscopic, narrow band imaging, and iodine staining individually and in combination for early esophageal cancer and precancerous lesions. Frontiers in Oncology 2026; 16 doi: 10.3389/fonc.2026.1810538
9	Shu-Qi Ren, Jin-Man Chen, Chuang Cai. Translational artificial intelligence in gastrointestinal and hepatic disorders: Advancing intelligent clinical decision-making for diagnosis, treatment, and prognosis. World Journal of Gastroenterology 2025; 31(36): 110742 doi: 10.3748/wjg.v31.i36.110742 Abstract(145) \| Core Tip(142) \| Full Article(HTML)(721) \| Full Article (PDF)-642K(232) \| Full Article with Cover (PDF)-904K(126) \| Full Article (XML)-426K(68) \| Audio-2063K(17) \| Peer-Review Report-290K(57) \| Answering Reviewers-197K(95) \| Times Cited (3) \| Total Visits (1261) \| Open
10	Xiaoyan Men, Yanfeng Wang, Yan Zhao, Huitao Zhang, Xiao Zhang. Endoscopy-Based Deep Learning Algorithms vs Endoscopists in Early Esophageal Squamous Cell Carcinoma Detection: A Systematic Review and Meta-Analysis. American Journal of Gastroenterology 2026; doi: 10.14309/ajg.0000000000004067
11	Yuqi Yang, Xiao Jia, Xi Wang, Pingdong Cao, Jian Zhu, Chuanxi Wang, Zhe Yang, Qiang Wen. AI in esophageal cancer: advances, barriers to clinical translation, and perspectives for digital health. Journal of Translational Medicine 2026; 24(1) doi: 10.1186/s12967-026-08270-3
12	Qing Li, Bing-Rong Liu. Application of artificial intelligence-assisted endoscopic detection of early esophageal cancer. World Chinese Journal of Digestology 2021; 29(24) doi: 10.11569/wcjd.v29.i24.1389 Abstract(1030) \| Core Tip(1009) \| Full Article(HTML)(5220) \| Times Cited (0) \| Total Visits (6304) \| Open
13	Xiang-Lei Yuan, Xian-Hui Zeng, Wei Liu, Yi Mou, Wan-Hong Zhang, Zheng-Duan Zhou, Xin Chen, Yan-Xing Hu, Bing Hu. Artificial intelligence for detecting and delineating the extent of superficial esophageal squamous cell carcinoma and precancerous lesions under narrow-band imaging (with video). Gastrointestinal Endoscopy 2023; 97(4) doi: 10.1016/j.gie.2022.12.003
14	Yongkang Tao, Long Fang, Geng Qin, Yingying Xu, Shuang Zhang, Xiangrong Zhang, Shiyu Du. Efficiency of endoscopic artificial intelligence in the diagnosis of early esophageal cancer. Thoracic Cancer 2024; 15(16) doi: 10.1111/1759-7714.15261
15	Paul T Kröner, Megan ML Engels, Benjamin S Glicksberg, Kipp W Johnson, Obaie Mzaik, Jeanin E van Hooft, Michael B Wallace, Hashem B El-Serag, Chayakrit Krittanawong. Artificial intelligence in gastroenterology: A state-of-the-art review. World Journal of Gastroenterology 2021; 27(40): 6794-6824 doi: 10.3748/wjg.v27.i40.6794 Abstract(1804) \| Core Tip(1305) \| Full Article(HTML)(18043) \| Full Article (PDF)-10786K(2006) \| Full Article (Word)-360K(269) \| Audio-1445K(21) \| Peer-Review Report-196K(322) \| Answering Reviewers-476K(458) \| Supplementary Material-1013K(417) \| Times Cited (152) \| Total Visits (21297) \| Open
16	Hemant Goyal, Syed A. A. Sherazi, Rupinder Mann, Zainab Gandhi, Abhilash Perisetti, Muhammad Aziz, Saurabh Chandan, Jonathan Kopel, Benjamin Tharian, Neil Sharma, Nirav Thosani. Scope of Artificial Intelligence in Gastrointestinal Oncology. Cancers 2021; 13(21) doi: 10.3390/cancers13215494
17	Min Liang, Chunhong Xu, Xinyan Zhang, Zongwang Zhang, Junli Cao. Effect of anesthesia assistance on the detection rate of precancerous lesions and early esophageal squamous cell cancer in esophagogastroduodenoscopy screening: A retrospective study based on propensity score matching. Frontiers in Medicine 2023; 10 doi: 10.3389/fmed.2023.1039979
18	Md. Mohaimenul Islam, Tahmina Nasrin Poly, Bruno Andreas Walther, Chih-Yang Yeh, Shabbir Seyed-Abdul, Yu-Chuan (Jack) Li, Ming-Chin Lin. Deep Learning for the Diagnosis of Esophageal Cancer in Endoscopic Images: A Systematic Review and Meta-Analysis. Cancers 2022; 14(23) doi: 10.3390/cancers14235996
19	Yunhao Li, Kimberly Ho, Thomas Ka-Luen Lui, Wai K. Leung. Comparison of Image-Enhanced Endoscopy Techniques for Colorectal Lesion Detection and Characterization: A Network Meta-Analysis of Randomized Controlled Trials. American Journal of Gastroenterology 2026; 121(4) doi: 10.14309/ajg.0000000000003848
20	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
21	Yuwei Pan, Lanying He, Weiqing Chen, Yongtao Yang. The current state of artificial intelligence in endoscopic diagnosis of early esophageal squamous cell carcinoma. Frontiers in Oncology 2023; 13 doi: 10.3389/fonc.2023.1198941
22	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
23	Junxiang Cao, Jiacheng Wang. TNM staging of esophageal cancer using fine-tuned pathology foundation models and multiple instance learning. Frontiers in Oncology 2026; 16 doi: 10.3389/fonc.2026.1832365
24	Yue Xu, Renquan Luo, Jiali Tang, Lu Liu, Haideng Yang, Jinbang Peng, Zhenzhen Wang, Xiuxiu Jin, Lingyan Shen, Lingling Yan, Jiacheng Li, Binbin Gu, Jun Wang, Xiang Jin, Xianbin Zhou, Ying Zhou, Jiaxiu Ying, Congni Zhu, Siyan Yan, Shaowei Li, Xinli Mao, Yu Zhang. Artificial Intelligence-Assisted Confocal Laser Endomicroscopy for Predicting Invasion Depth of Superficial Esophageal Mucosal Lesions: A Cohort Study. Clinical and Translational Gastroenterology 2026; 17(7) doi: 10.14309/ctg.0000000000001044
25	Suigu Tang, Xiaoyuan Yu, Chak Fong Cheang, Xiaoyu Ji, Hon Ho Yu, I Cheong Choi. CLELNet: A continual learning network for esophageal lesion analysis on endoscopic images. Computer Methods and Programs in Biomedicine 2023; 231 doi: 10.1016/j.cmpb.2023.107399
26	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
27	De Luo, Fei Kuang, Juan Du, Mengjia Zhou, Xiangdong Liu, Xinchen Luo, Yong Tang, Bo Li, Song Su. Artificial Intelligence–Assisted Endoscopic Diagnosis of Early Upper Gastrointestinal Cancer: A Systematic Review and Meta-Analysis. Frontiers in Oncology 2022; 12 doi: 10.3389/fonc.2022.855175
28	Ji-Han Qi, Shi-Ling Huang, Shi-Zhu Jin. Novel milestones for early esophageal carcinoma: From bench to bed. World Journal of Gastrointestinal Oncology 2024; 16(4): 1104-1118 doi: 10.4251/wjgo.v16.i4.1104 Abstract(683) \| Core Tip(700) \| Full Article(HTML)(2602) \| Full Article (PDF)-4723K(232) \| Full Article with Cover (PDF)-4949K(324) \| Full Article (XML)-268K(157) \| Audio-95K(10) \| Peer-Review Report-310K(154) \| Answering Reviewers-1577K(172) \| Supplementary Material-993K(151) \| Times Cited (7) \| Total Visits (3882) \| Open
29	Charalampos Theocharopoulos, Spyridon Davakis, Dimitrios C. Ziogas, Achilleas Theocharopoulos, Dimitra Foteinou, Adam Mylonakis, Ioannis Katsaros, Helen Gogas, Alexandros Charalabopoulos. Deep Learning for Image Analysis in the Diagnosis and Management of Esophageal Cancer. Cancers 2024; 16(19) doi: 10.3390/cancers16193285
30	Faure Rodríguez-Velásquez, Andrés Montoya-Durán, Nicole Bonilla, Jacobo Echeverri-Hoyos, Jaime A. Echeverri-Franco, Eduardo Tuta-Quintero. Applications of Artificial Intelligence in the Endoscopic Detection and Characterization of Early Esophageal Squamous Cell Carcinoma: A Scoping Review. Cancers 2026; 18(14) doi: 10.3390/cancers18142235
31	Wan-Yue Zhang, Yong-Jian Chang, Rui-Hua Shi. Artificial intelligence enhances the management of esophageal squamous cell carcinoma in the precision oncology era. World Journal of Gastroenterology 2024; 30(39): 4267-4280 doi: 10.3748/wjg.v30.i39.4267 Abstract(765) \| Core Tip(675) \| Full Article(HTML)(3784) \| Full Article (PDF)-1397K(199) \| Full Article with Cover (PDF)-1653K(176) \| Full Article (XML)-278K(155) \| Audio-404K(76) \| Peer-Review Report-175K(142) \| Answering Reviewers-202K(141) \| Times Cited (5) \| Total Visits (5318) \| Open
32	Hari Mohan Rai, Joon Yoo, Abdul Razaque. Comparative analysis of machine learning and deep learning models for improved cancer detection: A comprehensive review of recent advancements in diagnostic techniques. Expert Systems with Applications 2024; 255 doi: 10.1016/j.eswa.2024.124838
33	Chaoyi Shi, Shunhai Zhou, Xuanran Chen, Diyun Shen, GeSang ZhuoMa, Mingzhi Feng, Yan Sun, Jun Zhang. The impact of photographic image quantity on early upper gastrointestinal cancer detection during esophagogastroduodenoscopy. Scientific Reports 2025; 16(1) doi: 10.1038/s41598-025-29090-3
34	Jie Mao, Kexun Li, Zilong Qian, Jianzhe Zhang, Shengguai Gao, GuoMin Tian, Daiheng Yang, Xin Tang, Xin Yang, Can Li, Yapeng Xing, Jian Xu, Chengwei Bi. Artificial intelligence-assisted endoscopic diagnosis of esophageal squamous cell carcinoma. Frontiers in Artificial Intelligence 2026; 9 doi: 10.3389/frai.2026.1837887
35	月徐. Advances in Artificial Intelligence-Assisted Endoscopic Diagnosis of Esophageal Squamous Cell Carcinoma. Advances in Clinical Medicine 2026; 16(03) doi: 10.12677/acm.2026.1631187
36	Nuoya Zhou, Xianglei Yuan, Wei Liu, Qi Luo, Ruide Liu, Bing Hu. Artificial intelligence in endoscopic diagnosis of esophageal squamous cell carcinoma and precancerous lesions. Chinese Medical Journal 2025; 138(12) doi: 10.1097/CM9.0000000000003490
37	Ming-Wun Wong, Benjamin D. Rogers, Min-Xiang Liu, Wei-Yi Lei, Tso-Tsai Liu, Chih-Hsun Yi, Jui-Sheng Hung, Shu-Wei Liang, Chiu-Wang Tseng, Jen-Hung Wang, Ping-An Wu, Chien-Lin Chen. Application of Artificial Intelligence in Measuring Novel pH-Impedance Metrics for Optimal Diagnosis of GERD. Diagnostics 2023; 13(5) doi: 10.3390/diagnostics13050960
38	T. A. Sadulaeva, L. A. Edilgireeva, M. B. Bimurzaeva, A. O. Morozov. Use of artificial intelligence in diagnostic cystoscopy of bladder cancer. Cancer Urology 2023; 19(2) doi: 10.17650/1726-9776-2023-19-2-148-152
39	Shaleen Vasavada, Sharmila Anandasabapathy. Image Enhanced Endoscopy in Esophageal Squamous Cell Carcinoma. Foregut: The Journal of the American Foregut Society 2024; 4(1) doi: 10.1177/26345161231211752
40	Naoki Aoyama, Keiichiro Nakajo, Maasa Sasabe, Atsushi Inaba, Yuki Nakanishi, Hiroshi Seno, Tomonori Yano. Effects of artificial intelligence assistance on endoscopist performance: Comparison of diagnostic performance in superficial esophageal squamous cell carcinoma detection using video‐based models. DEN Open 2026; 6(1) doi: 10.1002/deo2.70083
41	Pierfrancesco Visaggi, Brigida Barberio, Dario Gregori, Danila Azzolina, Matteo Martinato, Cesare Hassan, Prateek Sharma, Edoardo Savarino, Nicola de Bortoli. Systematic review with meta‐analysis: artificial intelligence in the diagnosis of oesophageal diseases. Alimentary Pharmacology & Therapeutics 2022; 55(5) doi: 10.1111/apt.16778
42	Silvia Pecere, Sebastian Manuel Milluzzo, Gianluca Esposito, Emanuele Dilaghi, Andrea Telese, Leonardo Henry Eusebi. Applications of Artificial Intelligence for the Diagnosis of Gastrointestinal Diseases. Diagnostics 2021; 11(9) doi: 10.3390/diagnostics11091575
43	Bing Li, Yan-Yun Du, Wei-Min Tan, Dong-Li He, Zhi-Peng Qi, Hon-Ho Yu, Qiang Shi, Zhong Ren, Ming-Yan Cai, Bo Yan, Shi-Lun Cai, Yun-Shi Zhong. Effect of computer aided detection system on esophageal neoplasm diagnosis in varied levels of endoscopists. npj Digital Medicine 2025; 8(1) doi: 10.1038/s41746-025-01532-2
44	Amir Rafati Fard, Simon C. Williams, Kieran J. Smith, Jasneet K. Dhaliwal, Tomas Ferreira, Adrito Das, Joachim Starup-Hansen, John G. Hanrahan, Chan Hee Koh, Danyal Z. Khan, Danail Stoyanov, Hani J. Marcus. Comparing artificial intelligence and healthcare professional performance in surgical and interventional video analysis: a systematic review and meta-analysis. npj Digital Medicine 2026; 9(1) doi: 10.1038/s41746-026-02401-2
45	Nadia Guidozzi, Nainika Menon, Swathikan Chidambaram, Sheraz Rehan Markar. The role of artificial intelligence in the endoscopic diagnosis of esophageal cancer: a systematic review and meta-analysis. Diseases of the Esophagus 2023; 36(12) doi: 10.1093/dote/doad048
46	Jonathan S Galati, Robert J Duve, Matthew O'Mara, Seth A Gross. Artificial intelligence in gastroenterology: A narrative review. Artificial Intelligence in Gastroenterology 2022; 3(5): 117-141 doi: 10.35712/aig.v3.i5.117 Abstract(1635) \| Core Tip(1260) \| Full Article(HTML)(7058) \| Full Article (PDF)-1381K(614) \| Full Article (Word)-379K(102) \| Audio-143K(50) \| Peer-Review Report-248K(251) \| Answering Reviewers-210K(274) \| Supplementary Material-118K(256) \| Times Cited (1) \| Total Visits (9649) \| Open