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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Convolutional neural network for the diagnosis of early gastric cancer based on magnifying narrow band imaging
Lan Li, Yishu Chen, Zhe Shen, et al.
Gastric Cancer (2019) Vol. 23, Iss. 1, pp. 126-132
Open Access | Times Cited: 183

Showing 1-25 of 183 citing articles:

A scoping review of transfer learning research on medical image analysis using ImageNet
Mohammad Amin Morid, Alireza Borjali, Guilherme Del Fiol
Computers in Biology and Medicine (2020) Vol. 128, pp. 104115-104115
Open Access | Times Cited: 367
Artificial intelligence using convolutional neural networks for real-time detection of early esophageal neoplasia in Barrett’s esophagus (with video)
Rintaro Hashimoto, James Requa, Tyler Dao, et al.
Gastrointestinal Endoscopy (2020) Vol. 91, Iss. 6, pp. 1264-1271.e1
Closed Access | Times Cited: 186
Evaluation of the effects of an artificial intelligence system on endoscopy quality and preliminary testing of its performance in detecting early gastric cancer: a randomized controlled trial
Lianlian Wu, Xinqi He, Mei Liu, et al.
Endoscopy (2021) Vol. 53, Iss. 12, pp. 1199-1207
Open Access | Times Cited: 119
Convolutional Neural Network for Differentiating Gastric Cancer from Gastritis Using Magnified Endoscopy with Narrow Band Imaging
Yusuke Horiuchi, Kazuharu Aoyama, Yoshitaka Tokai, et al.
Digestive Diseases and Sciences (2019) Vol. 65, Iss. 5, pp. 1355-1363
Closed Access | Times Cited: 128
Application of artificial intelligence using a convolutional neural network for diagnosis of early gastric cancer based on magnifying endoscopy with narrow‐band imaging
Hiroya Ueyama, Yusuke Kato, Yoichi Akazawa, et al.
Journal of Gastroenterology and Hepatology (2020) Vol. 36, Iss. 2, pp. 482-489
Open Access | Times Cited: 118
Artificial intelligence in gastric cancer: Application and future perspectives
Penghui Niu, Lulu Zhao, Hongliang Wu, et al.
World Journal of Gastroenterology (2020) Vol. 26, Iss. 36, pp. 5408-5419
Open Access | Times Cited: 98
Artificial intelligence in gastric cancer: a systematic review
Peng Jin, Xiaoyan Ji, Wenzhe Kang, et al.
Journal of Cancer Research and Clinical Oncology (2020) Vol. 146, Iss. 9, pp. 2339-2350
Closed Access | Times Cited: 94
Artificial intelligence in gastroenterology: A state-of-the-art review
Paul T. Kröner, Megan Engels, Benjamin S. Glicksberg, et al.
World Journal of Gastroenterology (2021) Vol. 27, Iss. 40, pp. 6794-6824
Open Access | Times Cited: 91
Artificial Intelligence in Endoscopy
Yutaka Okagawa, Seiichiro Abe, Masayoshi Yamada, et al.
Digestive Diseases and Sciences (2021) Vol. 67, Iss. 5, pp. 1553-1572
Closed Access | Times Cited: 83
Accuracy of artificial intelligence–assisted detection of upper GI lesions: a systematic review and meta-analysis
Ka Luen Lui, Vivien Tsui, Wai K. Leung
Gastrointestinal Endoscopy (2020) Vol. 92, Iss. 4, pp. 821-830.e9
Closed Access | Times Cited: 75
Identifying early gastric cancer under magnifying narrow-band images with deep learning: a multicenter study
Hao Hu, Lixin Gong, Di Dong, et al.
Gastrointestinal Endoscopy (2020) Vol. 93, Iss. 6, pp. 1333-1341.e3
Closed Access | Times Cited: 75
Performance of a computer-aided diagnosis system in diagnosing early gastric cancer using magnifying endoscopy videos with narrow-band imaging (with videos)
Yusuke Horiuchi, Toshiaki Hirasawa, Naoki Ishizuka, et al.
Gastrointestinal Endoscopy (2020) Vol. 92, Iss. 4, pp. 856-865.e1
Closed Access | Times Cited: 74
A deep learning-based system for identifying differentiation status and delineating the margins of early gastric cancer in magnifying narrow-band imaging endoscopy
Tingsheng Ling, Lianlian Wu, Yiwei Fu, et al.
Endoscopy (2020) Vol. 53, Iss. 05, pp. 469-477
Closed Access | Times Cited: 73
Standalone performance of artificial intelligence for upper GI neoplasia: a meta-analysis
Julia Arribas, Giulio Antonelli, Leonardo Frazzoni, et al.
Gut (2020) Vol. 70, Iss. 8, pp. 1458-1468
Closed Access | Times Cited: 70
Endoscopic Image Classification Based on Explainable Deep Learning
Mukhtorov Doniyorjon, Rakhmonova Madinakhon, Shakhnoza Muksimova, et al.
Sensors (2023) Vol. 23, Iss. 6, pp. 3176-3176
Open Access | Times Cited: 39
The value of machine learning approaches in the diagnosis of early gastric cancer: a systematic review and meta-analysis
Yiheng Shi, Haohan Fan, Li Li, et al.
World Journal of Surgical Oncology (2024) Vol. 22, Iss. 1
Open Access | Times Cited: 11
A novel artificial intelligence-based endoscopic ultrasonography diagnostic system for diagnosing the invasion depth of early gastric cancer
Ryotaro Uema, Yoshito Hayashi, Takashi Kizu, et al.
Journal of Gastroenterology (2024) Vol. 59, Iss. 7, pp. 543-555
Open Access | Times Cited: 8
Artificial intelligence-assisted diagnosis of early gastric cancer: present practice and future prospects
Changda Lei, Wenqiang Sun, Kun Wang, et al.
Annals of Medicine (2025) Vol. 57, Iss. 1
Open Access | Times Cited: 1
Real-time artificial intelligence for detecting focal lesions and diagnosing neoplasms of the stomach by white-light endoscopy (with videos)
Lianlian Wu, Ming Xu, Xiaoda Jiang, et al.
Gastrointestinal Endoscopy (2021) Vol. 95, Iss. 2, pp. 269-280.e6
Closed Access | Times Cited: 51
Artificial Intelligence and Deep Learning for Upper Gastrointestinal Neoplasia
Prateek Sharma, Cesare Hassan
Gastroenterology (2021) Vol. 162, Iss. 4, pp. 1056-1066
Open Access | Times Cited: 45
An Investigational Approach for the Prediction of Gastric Cancer Using Artificial Intelligence Techniques: A Systematic Review
Priya Bhardwaj, Gaurav Bhandari, Yogesh Kumar, et al.
Archives of Computational Methods in Engineering (2022) Vol. 29, Iss. 6, pp. 4379-4400
Closed Access | Times Cited: 31
ALIEN: Attention-guided cross-resolution collaborative network for 3D gastric cancer segmentation in CT images
Zhihong Chen, Lisha Yao, Yanfen Cui, et al.
Biomedical Signal Processing and Control (2024) Vol. 96, pp. 106500-106500
Closed Access | Times Cited: 6
A Survey of Computer-Aided Tumor Diagnosis Based on Convolutional Neural Network
Yan Yan, Xujing Yao, Shuihua Wang, et al.
Biology (2021) Vol. 10, Iss. 11, pp. 1084-1084
Open Access | Times Cited: 38
Real-time use of artificial intelligence for diagnosing early gastric cancer by magnifying image-enhanced endoscopy: a multicenter diagnostic study (with videos)
Xinqi He, Lianlian Wu, Zehua Dong, et al.
Gastrointestinal Endoscopy (2021) Vol. 95, Iss. 4, pp. 671-678.e4
Closed Access | Times Cited: 37
Videomics: bringing deep learning to diagnostic endoscopy
Alberto Paderno, F. Christopher Holsinger, Cesare Piazza
Current Opinion in Otolaryngology & Head & Neck Surgery (2021) Vol. 29, Iss. 2, pp. 143-148
Closed Access | Times Cited: 36
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