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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:

GasHisSDB: A new gastric histopathology image dataset for computer aided diagnosis of gastric cancer
Weiming Hu, Chen Li, Xiaoyan Li, et al.
Computers in Biology and Medicine (2022) Vol. 142, pp. 105207-105207
Open Access | Times Cited: 64

Showing 1-25 of 64 citing articles:

MedViT: A robust vision transformer for generalized medical image classification
Omid Nejati Manzari, Hamid Ahmadabadi, Hossein Kashiani, et al.
Computers in Biology and Medicine (2023) Vol. 157, pp. 106791-106791
Open Access | Times Cited: 132
IL-MCAM: An interactive learning and multi-channel attention mechanism-based weakly supervised colorectal histopathology image classification approach
Haoyuan Chen, Chen Li, Xiaoyan Li, et al.
Computers in Biology and Medicine (2022) Vol. 143, pp. 105265-105265
Open Access | Times Cited: 103
Application of artificial intelligence for improving early detection and prediction of therapeutic outcomes for gastric cancer in the era of precision oncology
Zhe Wang, Yang Liu, Xing Niu
Seminars in Cancer Biology (2023) Vol. 93, pp. 83-96
Closed Access | Times Cited: 41
Vision Transformers for Computational Histopathology
Hongming Xu, Qi Xu, Fengyu Cong, et al.
IEEE Reviews in Biomedical Engineering (2023) Vol. 17, pp. 63-79
Closed Access | Times Cited: 39
A state-of-the-art survey of object detection techniques in microorganism image analysis: from classical methods to deep learning approaches
Pingli Ma, Chen Li, Md Mamunur Rahaman, et al.
Artificial Intelligence Review (2022) Vol. 56, Iss. 2, pp. 1627-1698
Open Access | Times Cited: 66
From modern CNNs to vision transformers: Assessing the performance, robustness, and classification strategies of deep learning models in histopathology
Maximilian Springenberg, Annika Frommholz, Markus Wenzel, et al.
Medical Image Analysis (2023) Vol. 87, pp. 102809-102809
Open Access | Times Cited: 36
CAM-VT: A Weakly supervised cervical cancer nest image identification approach using conjugated attention mechanism and visual transformer
Zizhen Fan, Xiangchen Wu, Changzhong Li, et al.
Computers in Biology and Medicine (2023) Vol. 162, pp. 107070-107070
Closed Access | Times Cited: 34
EBHI: A new Enteroscope Biopsy Histopathological H&E Image Dataset for image classification evaluation
Weiming Hu, Chen Li, Md Mamunur Rahaman, et al.
Physica Medica (2023) Vol. 107, pp. 102534-102534
Closed Access | Times Cited: 21
Applications of discriminative and deep learning feature extraction methods for whole slide image analysis: A survey
Khaled Al-Thelaya, Nauman Ullah Gilal, Mahmood Alzubaidi, et al.
Journal of Pathology Informatics (2023) Vol. 14, pp. 100335-100335
Open Access | Times Cited: 21
Role of Artificial Intelligence in Medical Image Analysis: A Review of Current Trends and Future Directions
Xin Li, Lei Zhang, Jingsi Yang, et al.
Journal of Medical and Biological Engineering (2024) Vol. 44, Iss. 2, pp. 231-243
Closed Access | Times Cited: 11
A deep architecture based on attention mechanisms for effective end-to-end detection of early and mature malaria parasites
Luca Zedda, Andrea Loddo, Cecilia Di Ruberto
Biomedical Signal Processing and Control (2024) Vol. 94, pp. 106289-106289
Open Access | Times Cited: 5
Microsatellite stable gastric cancer can be classified into two molecular subtypes with different immunotherapy response and prognosis based on gene sequencing and computational pathology
Zhiyi Ye, Xiao‐Yang Wu, Wei Zheng, et al.
Laboratory Investigation (2025), pp. 104101-104101
Closed Access
Deep learning-based image analysis in muscle histopathology using photo-realistic synthetic data
Leonid Mill, Oliver Aust, Jochen A. Ackermann, et al.
Communications Medicine (2025) Vol. 5, Iss. 1
Open Access
The artificial intelligence revolution in gastric cancer management: clinical applications
Runze Li, Jingfan Li, Yuman Wang, et al.
Cancer Cell International (2025) Vol. 25, Iss. 1
Open Access
Histopathological Gastric Cancer Detection on GasHisSDB Dataset Using Deep Ensemble Learning
Ming Ping Yong, Yan Chai Hum, Khin Wee Lai, et al.
Diagnostics (2023) Vol. 13, Iss. 10, pp. 1793-1793
Open Access | Times Cited: 15
EBHI-Seg: A novel enteroscope biopsy histopathological hematoxylin and eosin image dataset for image segmentation tasks
Liyu Shi, Xiaoyan Li, Weiming Hu, et al.
Frontiers in Medicine (2023) Vol. 10
Open Access | Times Cited: 13
CCF-GNN: A Unified Model Aggregating Appearance, Microenvironment, and Topology for Pathology Image Classification
Hongxiao Wang, Gang Huang, Zhuo Zhao, et al.
IEEE Transactions on Medical Imaging (2023) Vol. 42, Iss. 11, pp. 3179-3193
Closed Access | Times Cited: 13
A comprehensive survey of intestine histopathological image analysis using machine vision approaches
Yujie Jing, Chen Li, Tianming Du, et al.
Computers in Biology and Medicine (2023) Vol. 165, pp. 107388-107388
Closed Access | Times Cited: 13
A state-of-the-art survey of U-Net in microscopic image analysis: from simple usage to structure mortification
Jian Wu, Wanli Liu, Chen Li, et al.
Neural Computing and Applications (2023) Vol. 36, Iss. 7, pp. 3317-3346
Closed Access | Times Cited: 13
A novel approach for early gastric cancer detection using a hybrid of alexnet, extreme learning machine, and adjusted gorilla troops optimization
Daguang Fan, Huanfang Liang, Chongxiao Qu, et al.
Biomedical Signal Processing and Control (2024) Vol. 93, pp. 106126-106126
Closed Access | Times Cited: 4
VGG16-based intelligent image analysis in the pathological diagnosis of IgA nephropathy
Ying Chen, Yinyin Chen, Shuangshuang Fu, et al.
Journal of Radiation Research and Applied Sciences (2023) Vol. 16, Iss. 3, pp. 100626-100626
Open Access | Times Cited: 11
MCLNet: An multidimensional convolutional lightweight network for gastric histopathology image classification
Xuanshuo Fu, Shuyong Liu, Chao Li, et al.
Biomedical Signal Processing and Control (2022) Vol. 80, pp. 104319-104319
Closed Access | Times Cited: 17
The Swin-Transformer network based on focal loss is used to identify images of pathological subtypes of lung adenocarcinoma with high similarity and class imbalance
Yujun Wang, Furong Luo, Xing Yang, et al.
Journal of Cancer Research and Clinical Oncology (2023) Vol. 149, Iss. 11, pp. 8581-8592
Closed Access | Times Cited: 9
A comparative study of gastric histopathology sub-size image classification: From linear regression to visual transformer
Weiming Hu, Haoyuan Chen, Wanli Liu, et al.
Frontiers in Medicine (2022) Vol. 9
Open Access | Times Cited: 14
Exploiting Geometric Features via Hierarchical Graph Pyramid Transformer for Cancer Diagnosis using Histopathological Images
Mingxin Liu, Yunzan Liu, Pengbo Xu, et al.
IEEE Transactions on Medical Imaging (2024) Vol. 43, Iss. 8, pp. 2888-2900
Closed Access | Times Cited: 2
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