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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:

Generative models improve fairness of medical classifiers under distribution shifts
Sofia Ira Ktena, Olivia Wiles, Isabela Maria Carneiro Albuquerque, et al.
Nature Medicine (2024) Vol. 30, Iss. 4, pp. 1166-1173
Open Access | Times Cited: 26

Showing 1-25 of 26 citing articles:

Towards equitable AI in oncology
Vidya Sankar Viswanathan, Vani Parmar, Anant Madabhushi
Nature Reviews Clinical Oncology (2024) Vol. 21, Iss. 8, pp. 628-637
Closed Access | Times Cited: 10
A vision–language foundation model for the generation of realistic chest X-ray images
Christian Bluethgen, Pierre Chambon, Jean-Benoit Delbrouck, et al.
Nature Biomedical Engineering (2024)
Closed Access | Times Cited: 10
Self-improving generative foundation model for synthetic medical image generation and clinical applications
Jinzhuo Wang, Kai Wang, Yunfang Yu, et al.
Nature Medicine (2024)
Closed Access | Times Cited: 9
Synthetically enhanced: unveiling synthetic data's potential in medical imaging research
Bardia Khosravi, Frank Li, Theodorus Dapamede, et al.
EBioMedicine (2024) Vol. 104, pp. 105174-105174
Open Access | Times Cited: 8
Optimizing Rare Disease Gait Classification through Data Balancing and Generative AI: Insights from Hereditary Cerebellar Ataxia
Dante Trabassi, Stefano Filippo Castiglia, Fabiano Bini, et al.
Sensors (2024) Vol. 24, Iss. 11, pp. 3613-3613
Open Access | Times Cited: 8
Latent spaces of generative models for forensic age estimation
Anastasia Chernysheva, Christopher Gundler, Alexander Johannes Wiederhold, et al.
Rechtsmedizin (2025)
Open Access
A data-efficient strategy for building high-performing medical foundation models
Yuqi Sun, Weimin Tan, Zhuoyao Gu, et al.
Nature Biomedical Engineering (2025)
Closed Access
Bayesian Inference General Procedures for A Single-subject Test Study
Jie Li, Gary Green, Sarah J. A. Carr, et al.
Neuroscience Informatics (2025), pp. 100195-100195
Open Access
AI Image Generation Technology in Ophthalmology: Use, Misuse and Future Applications
Benjamin Phipps, Xavier Hadoux, Bin Sheng, et al.
Progress in Retinal and Eye Research (2025), pp. 101353-101353
Closed Access
Drop the shortcuts: image augmentation improves fairness and decreases AI detection of race and other demographics from medical images
Ryan Wang, Po‐Chih Kuo, Li-Ching Chen, et al.
EBioMedicine (2024) Vol. 102, pp. 105047-105047
Open Access | Times Cited: 4
Self-Supervised Learning Improves Accuracy and Data Efficiency for IMU-Based Ground Reaction Force Estimation
Tian Tan, Peter B. Shull, Jennifer L. Hicks, et al.
IEEE Transactions on Biomedical Engineering (2024) Vol. 71, Iss. 7, pp. 2095-2104
Open Access | Times Cited: 3
Synthetic Simplicity: Unveiling Bias in Medical Data Augmentation
Krishan Agyakari Raja Babu, Rachana Sathish, Mrunal Pattanaik, et al.
Lecture notes in computer science (2024), pp. 64-72
Closed Access | Times Cited: 3
The urgent need to accelerate synthetic data privacy frameworks for medical research
Anmol Arora, Siegfried Wagner, Rebecca Carpenter, et al.
The Lancet Digital Health (2024)
Open Access | Times Cited: 3
From Code to Clots: Applying Machine Learning to Clinical Aspects of Venous Thromboembolism Prevention, Diagnosis, and Management
Pavlina Chrysafi, Barbara D. Lam, Saskia Carton, et al.
Hämostaseologie (2024) Vol. 44, Iss. 06, pp. 429-445
Closed Access | Times Cited: 2
Using unlabeled data to enhance fairness of medical AI
Rajiv Movva, Pang Wei Koh, Emma Pierson
Nature Medicine (2024) Vol. 30, Iss. 4, pp. 944-945
Closed Access
Explainable AI for computational pathology identifies model limitations and tissue biomarkers.
Jakub Kaczmarzyk, Joel H. Saltz, Peter K. Koo
arXiv (Cornell University) (2024)
Open Access
A data-centric perspective to fair machine learning for healthcare
Haoran Zhang, Walter Gerych, Marzyeh Ghassemi
Nature Reviews Methods Primers (2024) Vol. 4, Iss. 1
Closed Access
Intersection of Performance, Interpretability, and Fairness in Neural Prototype Tree for Chest X-Ray Pathology Detection: Algorithm Development and Validation Study
Hongbo Chen, Myrtede Alfred, Andrew D. Brown, et al.
JMIR Formative Research (2024) Vol. 8, pp. e59045-e59045
Open Access
Machine learning methods for histopathological image analysis: Updates in 2024
Daisuke Komura, Mieko Ochi, Shumpei Ishikawa
Computational and Structural Biotechnology Journal (2024) Vol. 27, pp. 383-400
Open Access
Unbiasing Fairness Evaluation of Radiology AI Model
Yuxuan Liang, Hanqing Chao, Jiajin Zhang, et al.
Meta-Radiology (2024) Vol. 2, Iss. 3, pp. 100084-100084
Open Access
Artificial intelligence in cardiovascular imaging and intervention
Sandy Engelhardt, Salman Ul Hussan Dar, Lalith Sharan, et al.
Herz (2024) Vol. 49, Iss. 5, pp. 327-334
Closed Access
Harnessing the power of artificial intelligence to combat infectious diseases: Progress, challenges, and future outlook
Hang-Yu Zhou, Yaling Li, Jiaying Li, et al.
The Innovation Medicine (2024), pp. 100091-100091
Closed Access
Generative Modeling of the Circle of Willis Using 3D-StyleGAN
Orhun Utku Aydin, Adam Hilbert, Alexander Koch, et al.
NeuroImage (2024), pp. 120936-120936
Open Access
Redefining the Future of Cancer Care: Intelligent Oncology Unveiled
Bo Xu
(2024)
Open Access
Deep Generative Models for 3D Medical Image Synthesis
Paul Friedrich, Yannik Frisch, Philippe C. Cattin
(2024), pp. 255-278
Closed Access
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