World Journal of Gastroenterology - Baishideng Publishing Group

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For:	Zhang YH, Guo LJ, Yuan XL, Hu B. Artificial intelligence-assisted esophageal cancer management: Now and future. World J Gastroenterol 2020; 26(35): 5256-5271 [PMID: 32994686 DOI: 10.3748/wjg.v26.i35.5256]
URL:	https://www.wjgnet.com/1007-9327/full/v26/i35/5256.htm

(324) (327) (0) (0) (0) (9) (1) (11530) (51)

Number	Citing Articles
1	Constantine M. Poulos, Ryan Cassidy, Eamon Khatibifar, Erik Holzwanger, Lana Schumacher. The current state of artificial intelligence in robotic esophageal surgery. Mini-invasive Surgery 2025; doi: 10.20517/2574-1225.2024.42
2	Wei Sun, Peng Li, Yan Liang, Yadong Feng, Lingxiao Zhao. Detection of Image Artifacts Using Improved Cascade Region-Based CNN for Quality Assessment of Endoscopic Images. Bioengineering 2023; 10(11) doi: 10.3390/bioengineering10111288
3	B. Aishwarya, J. Priyanka, Mummadi Shyam Kumar Reddy, R. Mohan, Rohit Saluja, Divya Biligere Shivanna, Roopa S. Rao. Advances in Cancer Detection, Prediction, and Prognosis Using Artificial Intelligence and Machine Learning. 2025; doi: 10.1007/978-981-96-9346-7_2
4	Khalid M Bhatti, Zubair S Khanzada, Matta Kuzman, Syed M Ali, Syed Y Iftikhar, Peter Small. Diagnostic Performance of Artificial Intelligence-Based Models for the Detection of Early Esophageal Cancers in Barret’s Esophagus: A Meta-Analysis of Patient-Based Studies. Cureus 2021; doi: 10.7759/cureus.15447
5	Aanuoluwapo Clement David-Olawade, Nicholas Aderinto, Eghosasere Egbon, Gbolahan Deji Olatunji, Emmanuel Kokori, David B. Olawade. Enhancing endoscopic precision: the role of artificial intelligence in modern gastroenterology. Journal of Gastrointestinal Surgery 2025; 29(10) doi: 10.1016/j.gassur.2025.102195
6	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(1009) \| Core Tip(989) \| Full Article(HTML)(5125) \| Times Cited (0) \| Total Visits (6201) \| Open
7	Dan Ling, Tengfei Jiang, Junwei Sun, Yanfeng Wang, Yan Wang, Lidong Wang. An Ensemble Learning System Based on Stacking Strategy for Survival Risk Prediction of Patients with Esophageal Cancer. IRBM 2024; 45(6) doi: 10.1016/j.irbm.2024.100860
8	Lihao Zhang, Yinghao Zhong, Gang Yang, Lige Huang, Aijia Deng, Mengxin Ao, Jiabing Li. Artificial intelligence-assisted diagnosis and histopathological grading of bladder cancer: current status, challenges, and future directions. Frontiers in Digital Health 2026; 8 doi: 10.3389/fdgth.2026.1708289
9	Aiting Lin, Lirong Song, Ying Wang, Kai Yan, Hua Tang. Future prospects of deep learning in esophageal cancer diagnosis and clinical decision support (Review). Oncology Letters 2025; 29(6) doi: 10.3892/ol.2025.15039
10	Bindiya Chauhan, Tuhin James Paul. Biotechnology and Cancer Therapeutics. Interdisciplinary Biotechnological Advances 2025; doi: 10.1007/978-981-96-4959-4_6
11	Rua Y. Aburasain. Esophageal Cancer Classification in Initial Stages Using Deep and Transfer Learning. 2024 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET) 2024; doi: 10.1109/IC_ASET61847.2024.10596188
12	Philip H. Pucher, Bas P.L. Wijnhoven, Timothy J. Underwood, John V. Reynolds, Andrew R. Davies. Thinking through the multimodal treatment of localized oesophageal cancer: the point of view of the surgeon. Current Opinion in Oncology 2021; 33(4) doi: 10.1097/CCO.0000000000000751
13	Qin Huang, Yuqing Cheng, Edward Lew, Jiong Shi, Daniel Wiener, H. Christian Weber. Patients with esophageal adenocarcinoma showed better prognosis than those with adenocarcinoma of the gastroesophageal junction. Journal of Digestive Diseases 2023; 24(2) doi: 10.1111/1751-2980.13167
14	Ajitha Gladis K. P, Roja Ramani D, Mohana Suganthi N, Linu Babu P. Gastrointestinal tract disease detection via deep learning based structural and statistical features optimized hexa-classification model. Technology and Health Care 2024; 32(6) doi: 10.3233/THC-240603
15	Anmol Mohan, Zoha Asghar, Rabia Abid, Rasish Subedi, Karishma Kumari, Sushil Kumar, Koushik Majumder, Aqsa I. Bhurgri, Usha Tejwaney, Sarwan Kumar. Revolutionizing healthcare by use of artificial intelligence in esophageal carcinoma – a narrative review. Annals of Medicine & Surgery 2023; 85(10) doi: 10.1097/MS9.0000000000001175
16	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
17	Noor N. Al-Mayahi, Faisel G. Mohammed. Esophageal cancer segmentation based on FCM algorithm. 2ND INTERNATIONAL CONFERENCE FOR ENGINEERING SCIENCES AND INFORMATION TECHNOLOGY (ESIT 2022): ESIT2022 Conference Proceedings 2024; 3009 doi: 10.1063/5.0185313
18	Syed Wajid Aalam, Ab Basit Ahanger, Assif Assad, Muzafar A. Macha, Muzafar Rasool Bhat. Noninvasive prediction of metastasis in esophageal cancer using ensemble-based feature selection. International Journal of System Assurance Engineering and Management 2024; doi: 10.1007/s13198-024-02327-6
19	Yong Liu. Artificial intelligence-assisted endoscopic detection of esophageal neoplasia in early stage: The next step?. World Journal of Gastroenterology 2021; 27(14): 1392-1405 doi: 10.3748/wjg.v27.i14.1392 Abstract(1313) \| Core Tip(1166) \| Full Article(HTML)(5584) \| Full Article (PDF)-622K(674) \| Full Article (Word)-164K(327) \| Audio-1331K(21) \| Peer-Review Report-623K(279) \| Answering Reviewers-69K(320) \| Times Cited (13) \| Total Visits (7288) \| Open
20	Evgenia Mela, Dimitrios Tsapralis, Dimitrios Papaconstantinou, Panagiotis Sakarellos, Chrysovalantis Vergadis, Michail E. Klontzas, Ioannis Rouvelas, Antonios Tzortzakakis, Dimitrios Schizas. Current Role of Artificial Intelligence in the Management of Esophageal Cancer. Journal of Clinical Medicine 2025; 14(6) doi: 10.3390/jcm14061845
21	Jennifer A. Eckhoff, Hans F. Fuchs, Ozanan R. Meireles. Anwendung von künstlicher Intelligenz in der onkologischen Chirurgie des oberen Gastrointestinaltrakts. Die Onkologie 2023; 29(6) doi: 10.1007/s00761-023-01318-9
22	Kiran Raj M, Jyotsana Priyadarshani, Pratyaksh Karan, Saumyadwip Bandyopadhyay, Soumya Bhattacharya, Suman Chakraborty. Bio-inspired microfluidics: A review. Biomicrofluidics 2023; 17(5) doi: 10.1063/5.0161809
23	Ayrton Bangolo, Nikita Wadhwani, Vignesh K Nagesh, Shraboni Dey, Hadrian Hoang-Vu Tran, Izage Kianifar Aguilar, Auda Auda, Aman Sidiqui, Aiswarya Menon, Deborah Daoud, James Liu, Sai Priyanka Pulipaka, Blessy George, Flor Furman, Nareeman Khan, Adewale Plumptre, Imranjot Sekhon, Abraham Lo, Simcha Weissman. Impact of artificial intelligence in the management of esophageal, gastric and colorectal malignancies. Artificial Intelligence in Gastrointestinal Endoscopy 2024; 5(2): 90704 doi: 10.37126/aige.v5.i2.90704 Abstract(866) \| Core Tip(792) \| Full Article(HTML)(3413) \| Full Article (PDF)-488K(268) \| Full Article with Cover (PDF)-1691K(329) \| Full Article (XML)-264K(184) \| Audio-587K(35) \| Peer-Review Report-182K(130) \| Answering Reviewers-427K(135) \| Times Cited (2) \| Total Visits (4764) \| Open
24	Bassam Abboud, Rose Al Bacha, Joseph Bou Jaoude. Will artificial intelligence reach any limit in gastroenterology?. Artificial Intelligence in Gastroenterology 2024; 5(2): 91336 doi: 10.35712/aig.v5.i2.91336 Abstract(850) \| Core Tip(776) \| Full Article(HTML)(1518) \| Full Article (PDF)-431K(171) \| Full Article with Cover (PDF)-700K(292) \| Full Article (XML)-180K(132) \| Audio-1465K(14) \| Peer-Review Report-215K(136) \| Answering Reviewers-18K(130) \| Times Cited (1) \| Total Visits (2113) \| Open
25	Kengo Kanetaka, Susumu Eguchi, Tomohiko Adachi, Kaito Tasaki, Masayuki Fukumoto, Yasuhiko Nakao, Taro Akashi, Shinichiro Kobayashi, Ken Kurisaki. 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(70) \| Core Tip(93) \| Full Article(HTML)(315) \| Full Article (PDF)-648K(46) \| Full Article with Cover (PDF)-1017K(33) \| Full Article (XML)-239K(40) \| Audio-1996K(26) \| Peer-Review Report-270K(32) \| Answering Reviewers-297K(28) \| Times Cited (1) \| Total Visits (534) \| Open
26	Dong Huang, Xiaopan Xu, Peng Du, Yuefei Feng, Xi Zhang, Hongbing Lu, Yang Liu. Radiomics-based T-staging of hollow organ cancers. Frontiers in Oncology 2023; 13 doi: 10.3389/fonc.2023.1191519
27	P. Linu Babu, S. Jana. Gastrointestinal tract disease detection via deep learning based Duo-Feature Optimized Hexa-Classification model. Biomedical Signal Processing and Control 2025; 100 doi: 10.1016/j.bspc.2024.106994
28	Ashok Kumar, Kush S Parikh. Nomographic predictive models for complications after minimally invasive esophagectomy: Current status and future perspectives. World Journal of Gastrointestinal Surgery 2025; 17(12): 113586 doi: 10.4240/wjgs.v17.i12.113586 Abstract(92) \| Core Tip(76) \| Full Article(HTML)(258) \| Full Article (PDF)-529K(352) \| Full Article with Cover (PDF)-854K(37) \| Full Article (XML)-240K(37) \| Audio-287K(17) \| Peer-Review Report-289K(38) \| Answering Reviewers-82K(51) \| Times Cited (1) \| Total Visits (752) \| Open
29	Dan Gao, Yu-ping Wu, Tian-wu Chen. Review and prospects of new progress in intelligent imaging research on lymph node metastasis in esophageal carcinoma. Meta-Radiology 2024; 2(2) doi: 10.1016/j.metrad.2024.100081
30	Hsu-Heng Yen, Ping-Yu Wu, Pei-Yuan Su, Chia-Wei Yang, Yang-Yuan Chen, Mei-Fen Chen, Wen-Chen Lin, Cheng-Lun Tsai, Kang-Ping Lin. Performance Comparison of the Deep Learning and the Human Endoscopist for Bleeding Peptic Ulcer Disease. Journal of Medical and Biological Engineering 2021; 41(4) doi: 10.1007/s40846-021-00608-0
31	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
32	Lingyu Wang, Ning Ding, Pengfei Zuo, Xuenan Wang, B Karunakara Rai. Application and Challenges of Artificial Intelligence in Medical Imaging. 2022 International Conference on Knowledge Engineering and Communication Systems (ICKES) 2022; doi: 10.1109/ICKECS56523.2022.10059898
33	Jinming Wang, Qigang Long, Yan Liang, Jie Song, Yadong Feng, Peng Li, Wei Sun, Lingxiao Zhao. AI-assisted identification of intrapapillary capillary loops in magnification endoscopy for diagnosing early-stage esophageal squamous cell carcinoma: a preliminary study. Medical & Biological Engineering & Computing 2023; 61(7) doi: 10.1007/s11517-023-02777-3
34	Oswald Ndi Nfor, Pei-Ming Huang, Ming-Fang Wu, Ke-Cheng Chen, Ying-Hsiang Chou, Mong-Wei Lin, Ji-Han Zhong, Shuenn-Wen Kuo, Yu-Kwang Lee, Chih-Hung Hsu, Jang-Ming Lee, Yung-Po Liaw. Personalized prediction of esophageal cancer risk based on virtually generated alcohol data. Journal of Translational Medicine 2025; 23(1) doi: 10.1186/s12967-025-06383-9
35	Yuan Gui, Jing Zhang. Research progress of deep learning based on magnetic resonance imaging in meningioma. Magnetic Resonance Materials in Physics, Biology and Medicine 2025; 39(4) doi: 10.1007/s10334-025-01307-6
36	Nawaf R. Alharbe, Raafat M. Munshi, Manal M. Khayyat, Mashael M. Khayyat, Saadia Hassan Abdalaha Hamza, Abeer A. Aljohani, Laxmi Lydia. Atom Search Optimization with the Deep Transfer Learning-Driven Esophageal Cancer Classification Model. Computational Intelligence and Neuroscience 2022; 2022 doi: 10.1155/2022/4629178
37	Alia P. Qureshi, Thitiporn Chobarporn, Daniela Molena. Evolution of the treatment of esophageal cancer: artificial intelligence and the role of sentinel lymph node assessment in esophageal cancer. Artificial Intelligence Surgery 2024; 4(2) doi: 10.20517/ais.2023.37
38	Keyi Ji, Suhui Wu, Jiayao Yuan, Yu Wang, Genlin Li, Linlin Wang, Shuncai Wang, Longjie Wang, Hanbing Li, Chengbao Wang. L-Selenomethylselenocysteine Exerts Inhibitory Effects on the Progression of Esophageal Cancer by Targeting the PI3K/AKT Signaling Pathway. Recent Patents on Anti-Cancer Drug Discovery 2026; 21(2) doi: 10.2174/0115748928355152250527060605
39	Alin-Ionut Piraianu, Ana Fulga, Carmina Liana Musat, Oana-Roxana Ciobotaru, Diana Gina Poalelungi, Elena Stamate, Octavian Ciobotaru, Iuliu Fulga. Enhancing the Evidence with Algorithms: How Artificial Intelligence Is Transforming Forensic Medicine. Diagnostics 2023; 13(18) doi: 10.3390/diagnostics13182992
40	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
41	Yu Yang, Yu-Xuan Li, Ren-Qi Yao, Xiao-Hui Du, Chao Ren. Artificial intelligence in small intestinal diseases: Application and prospects. World Journal of Gastroenterology 2021; 27(25): 3734-3747 doi: 10.3748/wjg.v27.i25.3734 Abstract(1337) \| Core Tip(1199) \| Full Article(HTML)(4681) \| Full Article (PDF)-710K(698) \| Full Article (Word)-170K(651) \| Audio-753K(19) \| Peer-Review Report-866K(239) \| Answering Reviewers-398K(296) \| Times Cited (16) \| Total Visits (7099) \| Open
42	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
43	Fang Liao, Shuangbin Yu, Ying Zhou, Benying Feng. A machine learning model predicting candidates for surgical treatment modality in patients with distant metastatic esophageal adenocarcinoma: A propensity score-matched analysis. Frontiers in Oncology 2022; 12 doi: 10.3389/fonc.2022.862536
44	Maximilian Berlet, Jonas Fuchtmann, Alissa Jell, Dirk Wilhelm, Helmut Friess. Potenzial und Herausforderung - Robotik und KI in der Chirurgie. Gastro-News 2025; 12(3) doi: 10.1007/s15036-025-3870-5
45	Alexander Pohlman, Zaid M. Abdelsattar. The Use of Artificial Intelligence and Machine Learning in Thoracic Surgery. Thoracic Surgery Clinics 2025; 35(4) doi: 10.1016/j.thorsurg.2025.07.006
46	Jennifer A. Eckhoff, Hans F. Fuchs, Ozanan R. Meireles. Anwendung von künstlicher Intelligenz in der onkologischen Chirurgie des oberen Gastrointestinaltrakts. Wiener klinisches Magazin 2024; 27(5-6) doi: 10.1007/s00740-023-00504-0
47	Bin Guo, Haitao Han, Zhaoyang Yan, Qingyu Sheng, Xinran Wang, Jiankun He, Nan Mu, Xing Cui, Jidong Zhao, Xin Chen, Ming He, Qi Zhao. The prognostic value of tumor deposits in esophageal squamous cell carcinoma: A propensity score matching study. European Journal of Surgical Oncology 2026; 52(2) doi: 10.1016/j.ejso.2025.111353
48	Qiang Shen, Hongyu Chen. A novel risk classification system based on the eighth edition of TNM frameworks for esophageal adenocarcinoma patients: A deep learning approach. Frontiers in Oncology 2022; 12 doi: 10.3389/fonc.2022.887841
49	JunHo Lee, Hanna Lee, Jun-won Chung. The Role of Artificial Intelligence in Gastric Cancer: Surgical and Therapeutic Perspectives: A Comprehensive Review. Journal of Gastric Cancer 2023; 23(3) doi: 10.5230/jgc.2023.23.e31
50	Magdalena Leśniewska, Rafał Patryn, Agnieszka Kopystecka, Ilona Kozioł, Julia Budzyńska. Third Eye? The Assistance of Artificial Intelligence (AI) in the Endoscopy of Gastrointestinal Neoplasms. Journal of Clinical Medicine 2023; 12(21) doi: 10.3390/jcm12216721
51	Shi-Zhu Jin, Ning Li. Artificial intelligence and early esophageal cancer. Artificial Intelligence in Gastrointestinal Endoscopy 2021; 2(5): 198-210 doi: 10.37126/aige.v2.i5.198 Abstract(1414) \| Core Tip(1307) \| Full Article(HTML)(2973) \| Full Article (PDF)-2053K(441) \| Full Article (Word)-199K(306) \| Audio-1114K(16) \| Peer-Review Report-221K(217) \| Answering Reviewers-793K(215) \| Times Cited (1) \| Total Visits (5239) \| Open