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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 foundation model for clinical-grade computational pathology and rare cancers detection
Eugene Vorontsov, Alican Bozkurt, Adam Casson, et al.
Nature Medicine (2024) Vol. 30, Iss. 10, pp. 2924-2935
Open Access | Times Cited: 40

Showing 1-25 of 40 citing articles:

A vision–language foundation model for precision oncology
Jinxi Xiang, Xiyue Wang, Xiaoming Zhang, et al.
Nature (2025)
Closed Access | Times Cited: 1
Exploring scalable medical image encoders beyond text supervision
Fernando Pérez‐García, Harshita Sharma, Sam Bond-Taylor, et al.
Nature Machine Intelligence (2025)
Closed Access | Times Cited: 1
Unlocking the potential of digital pathology: Novel baselines for compression
Maximilian Fischer, Peter Neher, Peter J. Schüffler, et al.
Journal of Pathology Informatics (2025), pp. 100421-100421
Open Access | Times Cited: 1
A comprehensive evaluation of histopathology foundation models for ovarian cancer subtype classification
Jack Breen, Katrina J. Allen, Kieran Zucker, et al.
npj Precision Oncology (2025) Vol. 9, Iss. 1
Open Access | Times Cited: 1
Deep learning for predicting prognostic consensus molecular subtypes in cervical cancer from histology images
Ruoyu Wang, Gozde N. Gunesli, Vilde E. Skingen, et al.
npj Precision Oncology (2025) Vol. 9, Iss. 1
Open Access
When multiple instance learning meets foundation models: Advancing histological whole slide image analysis
Hongming Xu, Mingkang Wang, Duan‐Bo Shi, et al.
Medical Image Analysis (2025) Vol. 101, pp. 103456-103456
Open Access
Contrastive Learning for Omics-guided Whole-slide Visual Embedding Representation
Suwan Yu, Yooeun Kim, Hyun-Seok Kim, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2025)
Open Access
The tumour histopathology “glossary” for AI developers
S. Mandal, Ann‐Marie Baker, Trevor A. Graham, et al.
PLoS Computational Biology (2025) Vol. 21, Iss. 1, pp. e1012708-e1012708
Open Access
Evaluating ChatGPT’s diagnostic potential for pathology images
Liya Ding, Lei Fan, Miao Shen, et al.
Frontiers in Medicine (2025) Vol. 11
Open Access
Unraveling complexity and leveraging opportunities in uncommon breast cancer subtypes
Fresia Pareja, Rohit Bhargava, Virginia F. Borges, et al.
npj Breast Cancer (2025) Vol. 11, Iss. 1
Open Access
Validation of histopathology foundation models through whole slide image retrieval
Saghir Alfasly, Ghazal Alabtah, Sobhan Hemati, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Artificial intelligence in digital pathology — time for a reality check
Arpit Aggarwal, Satvika Bharadwaj, Germán Corredor, et al.
Nature Reviews Clinical Oncology (2025)
Closed Access
Transformative Approaches in Breast Cancer Detection: Integrating Transformers into Computer-Aided Diagnosis for Histopathological Classification
Majed Alwateer, Amna Bamaqa, Mohammad Farsi, et al.
Bioengineering (2025) Vol. 12, Iss. 3, pp. 212-212
Open Access
Artificial intelligence for medicine 2025: Navigating the endless frontier
Jiyan Dai, Huiyu Xu, Tao Chen, et al.
The Innovation Medicine (2025), pp. 100120-100120
Closed Access
A novel framework for the automated characterization of Gram-stained blood culture slides using a large-scale vision transformer
J. McMahon, Naofumi Tomita, Elizabeth S. Tatishev, et al.
Journal of Clinical Microbiology (2025)
Open Access
General lightweight framework for vision foundation model supporting multi-task and multi-center medical image analysis
Senliang Lu, Yehang Chen, Yuan Chen, et al.
Nature Communications (2025) Vol. 16, Iss. 1
Open Access
UniSAL: Unified Semi-supervised Active Learning for histopathological image classification
Lanfeng Zhong, Kun Qian, Xin Liao, et al.
Medical Image Analysis (2025) Vol. 102, pp. 103542-103542
Closed Access
MuCST: restoring and integrating heterogeneous morphology images and spatial transcriptomics data with contrastive learning
Yu Wang, Zaiyi Liu, Xiaoke Ma
Genome Medicine (2025) Vol. 17, Iss. 1
Open Access
A Multimodal Framework for Assessing the Link between Pathomics, Transcriptomics, and Pancreatic Cancer Mutations
Francesco Berloco, Gian Maria Zaccaria, Nicola Altini, et al.
Computerized Medical Imaging and Graphics (2025), pp. 102526-102526
Closed Access
Computational pathology: A comprehensive review of recent developments in digital and intelligent pathology
Qinqin Huang, Sean M. Wu, Zhenyu Ou, et al.
(2025)
Closed Access
Non-Generative Artificial Intelligence (AI) in Medicine: Advancements and Applications in Supervised and Unsupervised Machine Learning
Liron Pantanowitz, Thomas M. Pearce, Ibrahim Abukhiran, et al.
Modern Pathology (2024), pp. 100680-100680
Open Access | Times Cited: 3
Machine learning for medical image classification
Gulam Mohammed Husain, Jonathan Mayer, Molly Bekbolatova, et al.
Academia Medicine (2024) Vol. 1, Iss. 4
Closed Access | Times Cited: 3
Review of deep learning-based pathological image classification: From task-specific models to foundation models
Dan‐Yang Yuan, Kaixing Yang, Taiyuan Hu, et al.
Future Generation Computer Systems (2024), pp. 107578-107578
Closed Access | Times Cited: 2
Deep learning using histological images for gene mutation prediction in lung cancer: a multicentre retrospective study
Yu Zhao, Shan Xiong, Qin Ren, et al.
The Lancet Oncology (2024) Vol. 26, Iss. 1, pp. 136-146
Closed Access | Times Cited: 2
The age of foundation models
Jana Lipková, Jakob Nikolas Kather
Nature Reviews Clinical Oncology (2024) Vol. 21, Iss. 11, pp. 769-770
Closed Access | Times Cited: 1
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