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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:

A survey on graph-based deep learning for computational histopathology
David Ahmedt‐Aristizabal, Mohammad Ali Armin, Simon Denman, et al.
Computerized Medical Imaging and Graphics (2021) Vol. 95, pp. 102027-102027
Open Access | Times Cited: 75

Showing 1-25 of 75 citing articles:

Artificial intelligence for multimodal data integration in oncology
Jana Lipková, Richard J. Chen, Bowen Chen, et al.
Cancer Cell (2022) Vol. 40, Iss. 10, pp. 1095-1110
Open Access | Times Cited: 312
Graph representation learning in biomedicine and healthcare
Michelle M. Li, Kexin Huang, Marinka Žitnik
Nature Biomedical Engineering (2022) Vol. 6, Iss. 12, pp. 1353-1369
Open Access | Times Cited: 159
Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future
David Ahmedt‐Aristizabal, Mohammad Ali Armin, Simon Denman, et al.
Sensors (2021) Vol. 21, Iss. 14, pp. 4758-4758
Open Access | Times Cited: 157
Artificial intelligence for digital and computational pathology
Andrew H. Song, Guillaume Jaume, Drew F. K. Williamson, et al.
Nature Reviews Bioengineering (2023) Vol. 1, Iss. 12, pp. 930-949
Closed Access | Times Cited: 82
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: 41
Multimodal data integration for oncology in the era of deep neural networks: a review
Asim Waqas, Aakash Tripathi, Ravi P. Ramachandran, et al.
Frontiers in Artificial Intelligence (2024) Vol. 7
Open Access | Times Cited: 22
Graph neural networks in histopathology: Emerging trends and future directions
Siemen Brussee, Giorgio Buzzanca, Anne M.R. Schrader, et al.
Medical Image Analysis (2025) Vol. 101, pp. 103444-103444
Open Access | Times Cited: 3
A Convolutional Neural Network and Graph Convolutional Network Based Framework for Classification of Breast Histopathological Images
Zhiyang Gao, Zhiyang Lu, Jun Wang, et al.
IEEE Journal of Biomedical and Health Informatics (2022) Vol. 26, Iss. 7, pp. 3163-3173
Closed Access | Times Cited: 40
Histopathology Whole Slide Image Analysis with Heterogeneous Graph Representation Learning
Tsai Hor Chan, Fernando Julio Cendra, Lan Ma, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2023), pp. 15661-15670
Open Access | Times Cited: 39
Revolutionizing Digital Pathology With the Power of Generative Artificial Intelligence and Foundation Models
Asim Waqas, Marilyn M. Bui, Eric F. Glassy, et al.
Laboratory Investigation (2023) Vol. 103, Iss. 11, pp. 100255-100255
Open Access | Times Cited: 33
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: 23
Dynamic Graph Representation with Knowledge-Aware Attention for Histopathology Whole Slide Image Analysis
Jiawen Li, Yuxuan Chen, Hongbo Chu, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024), pp. 11323-11332
Closed Access | Times Cited: 8
Screening of normal endoscopic large bowel biopsies with interpretable graph learning: a retrospective study
Simon Graham, Fayyaz Minhas, Mohsin Bilal, et al.
Gut (2023) Vol. 72, Iss. 9, pp. 1709-1721
Open Access | Times Cited: 19
A comprehensive review of the deep learning-based tumor analysis approaches in histopathological images: segmentation, classification and multi-learning tasks
Heba Abdel-Nabi, Mostafa Z. Ali, Arafat Awajan, et al.
Cluster Computing (2023) Vol. 26, Iss. 5, pp. 3145-3185
Closed Access | Times Cited: 18
Continuous Human Action Recognition for Human-machine Interaction: A Review
Harshala Gammulle, David Ahmedt‐Aristizabal, Simon Denman, et al.
ACM Computing Surveys (2023) Vol. 55, Iss. 13s, pp. 1-38
Open Access | Times Cited: 18
An aggregation of aggregation methods in computational pathology
Mohsin Bilal, Robert Jewsbury, Ruoyu Wang, et al.
Medical Image Analysis (2023) Vol. 88, pp. 102885-102885
Open Access | Times Cited: 16
Boosting short term electric load forecasting of high & medium voltage substations with visibility graphs and graph neural networks
Νικόλαος Γιαμαρέλος, Elias N. Zois
Sustainable Energy Grids and Networks (2024) Vol. 38, pp. 101304-101304
Closed Access | Times Cited: 7
Context-Aware Self-Supervised Learning of Whole Slide Images
Milan Aryal, Nasim Soltani
IEEE Transactions on Artificial Intelligence (2024) Vol. 5, Iss. 8, pp. 4111-4120
Open Access | Times Cited: 6
MFAGCN: A new framework for identifying power grid branch parameters
Min Xia, Zhiwei Wang, Min Lu, et al.
Electric Power Systems Research (2022) Vol. 207, pp. 107855-107855
Closed Access | Times Cited: 22
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
Not seeing the trees for the forest. The impact of neighbours on graph-based configurations in histopathology
Olga Fourkioti, Matt De Vries, Reed Naidoo, et al.
BMC Bioinformatics (2025) Vol. 26, Iss. 1
Open Access
USING CONVOLUTIONAL NETWORK IN GRAPHICAL MODEL DETECTION OF AUTISM DISORDERS WITH FUZZY INFERENCE SYSTEMS
S. Rajaprakash, C. Bagath Basha, C. Sunitha Ram, et al.
Intelligence-Based Medicine (2025) Vol. 11, pp. 100213-100213
Open Access
HistoGraphCoarse: Strategizing Graph Coarsening Techniques for Efficient Analysis of Gigapixel Histopathological Images
Ekta Srivastava, Syed Mohammed Danish, Arjun Kumar, et al.
Lecture notes in computer science (2025), pp. 84-95
Closed Access
An adaptive feature fusion framework of CNN and GNN for histopathology images classification
Linhao Li, Min Xu, Shuai Chen, et al.
Computers & Electrical Engineering (2025) Vol. 123, pp. 110186-110186
Closed Access
Deep learning for efficient high-resolution image processing: A systematic review
Albert Dede, Henry Nunoo‐Mensah, Eric Tutu Tchao, et al.
Intelligent Systems with Applications (2025), pp. 200505-200505
Open Access
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