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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:

Risk of Bias in Chest Radiography Deep Learning Foundation Models
Ben Glocker, Charles Jones, Mélanie Roschewitz, et al.
Radiology Artificial Intelligence (2023) Vol. 5, Iss. 6
Open Access | Times Cited: 27

Showing 1-25 of 27 citing articles:

The value of standards for health datasets in artificial intelligence-based applications
Anmol Arora, Joseph Alderman, Joanne Palmer, et al.
Nature Medicine (2023) Vol. 29, Iss. 11, pp. 2929-2938
Open Access | Times Cited: 90
Bidirectional Encoder Representations from Transformers in Radiology: A Systematic Review of Natural Language Processing Applications
Larisa Gorenstein, Eli Konen, Michael Green, et al.
Journal of the American College of Radiology (2024) Vol. 21, Iss. 6, pp. 914-941
Closed Access | Times Cited: 17
Demographic bias in misdiagnosis by computational pathology models
Anurag Vaidya, Richard J. Chen, Drew F. K. Williamson, et al.
Nature Medicine (2024) Vol. 30, Iss. 4, pp. 1174-1190
Closed Access | Times Cited: 15
Sex-based bias in artificial intelligence-based segmentation models in clinical oncology
Florence X. Doo, W G Naranjo, Thodoris Kapouranis, et al.
Clinical Oncology (2025) Vol. 39, pp. 103758-103758
Closed Access
Domain shift, domain adaptation, and generalization
Jonas Richiardi, Veronica Ravano, Nataliia Molchanova, et al.
Elsevier eBooks (2025), pp. 127-151
Closed Access
Foundation Models in Radiology: What, How, Why, and Why Not
Magdalini Paschali, Zhihong Chen, Louis Blankemeier, et al.
Radiology (2025) Vol. 314, Iss. 2
Closed Access
Human-AI Symbiosis: A Path Forward to Improve Chest Radiography and the Role of Radiologists in Patient Care
Warren B. Gefter, Mathias Prokop, Joon Beom Seo, et al.
Radiology (2024) Vol. 310, Iss. 1
Closed Access | Times Cited: 4
Te Oranga Pūkahukahu research programme: intentional steps towards a national equity-focused lung cancer screening programme in Aotearoa New Zealand
Kate Parker, Karen Bartholomew, Peter Sandiford, et al.
Journal of the Royal Society of New Zealand (2025), pp. 1-16
Open Access
Doctor’s Orders—Why Radiologists Should Consider Adjusting Commercial Machine Learning Applications in Chest Radiography to Fit Their Specific Needs
Frank Philipp Schweikhard, Anika Kosanke, Sandra Lange, et al.
Healthcare (2024) Vol. 12, Iss. 7, pp. 706-706
Open Access | Times Cited: 2
Digital twins as a unifying framework for surgical data science: the enabling role of geometric scene understanding
Hao Ding, Lalithkumar Seenivasan, Benjamin D. Killeen, et al.
Artificial Intelligence Surgery (2024) Vol. 4, Iss. 3, pp. 109-38
Open Access | Times Cited: 2
Independent evaluation of the accuracy of 5 artificial intelligence software for detecting lung nodules on chest X-rays
Kirill M. Arzamasov, Yuriy А. Vasilev, Maria A. Zelenova, et al.
Quantitative Imaging in Medicine and Surgery (2024) Vol. 14, Iss. 8, pp. 5288-5303
Open Access | Times Cited: 2
How do deep-learning models generalize across populations? Cross-ethnicity generalization of COPD detection
Sílvia D. Almeida, Tobias Norajitra, Carsten T. Lüth, et al.
Insights into Imaging (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 1
Low-Rank Knowledge Decomposition for Medical Foundation Models
Yuhang Zhou, Haolin Li, Siyuan Du, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024), pp. 11611-11620
Closed Access | Times Cited: 1
Algorithm-agnostic significance testing in supervised learning with multimodal data
Lucas Kook, Anton Rask Lundborg
Briefings in Bioinformatics (2024) Vol. 25, Iss. 6
Open Access | Times Cited: 1
Bioimaging and-the future of whole-organismal developmental physiology
Oliver Tills, Ziad Ibbini, John I. Spicer
Comparative Biochemistry and Physiology Part A Molecular & Integrative Physiology (2024), pp. 111783-111783
Open Access | Times Cited: 1
Special Section Guest Editorial: Global Health, Bias, and Diversity in AI in Medical Imaging
Judy Wawira Gichoya, Rui Carlos Sá, Ronald M. Summers, et al.
Journal of Medical Imaging (2024) Vol. 10, Iss. 06
Open Access
Weak Supervision, Strong Results: Achieving High Performance in Intracranial Hemorrhage Detection with Fewer Annotation Labels
Kareem A. Wahid, David Fuentes
Radiology Artificial Intelligence (2024) Vol. 6, Iss. 1
Open Access
Transformer Unlocks the Gateway to Advanced Research: Predicting Diseases on Chest Radiographs Using Multimodal Data
Kengo Takahashi, Takuma Usuzaki, Ryusei Inamori
Radiology (2024) Vol. 310, Iss. 2
Closed Access
Towards Aleatoric and Epistemic Uncertainty in Medical Image Classification
Timo Löhr, Michael Ingrisch, Eyke Hüllermeier
Lecture notes in computer science (2024), pp. 145-155
Closed Access
The Importance of Model Inspection for Better Understanding Performance Characteristics of Graph Neural Networks
Nairouz Shehata, Carolina Piçarra, Anees Kazi, et al.
(2024), pp. 1-5
Open Access
Real-World evaluation of an AI triaging system for chest X-rays: A prospective clinical study
S. Sridharan, Alicia Seah Xin Hui, Narayan Venkataraman, et al.
European Journal of Radiology (2024) Vol. 181, pp. 111783-111783
Closed Access
AI Fairness in Medical Imaging: Controlling for Disease Severity
Pritam Mukherjee, Ronald M. Summers
Lecture notes in computer science (2024), pp. 24-33
Closed Access
Slicing Through Bias: Explaining Performance Gaps in Medical Image Analysis Using Slice Discovery Methods
Vincent Olesen, Nina Weng, Aasa Feragen, et al.
Lecture notes in computer science (2024), pp. 3-13
Closed Access
Detection of Pneumonia in Children through Chest Radiographs using Artificial Intelligence in a Low-Resource Setting: A Pilot Study
Taofeeq Oluwatosin Togunwa, Abdulhammed Opeyemi Babatunde, Oluwatosin Ebunoluwa Fatade, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Bias in Foundation Models: Primum Non Nocere or Caveat Emptor?
Julianna M. Czum, Shane Parr
Radiology Artificial Intelligence (2023) Vol. 5, Iss. 6
Open Access | Times Cited: 1
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