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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:

Bias in machine learning models can be significantly mitigated by careful training: Evidence from neuroimaging studies
Rongguang Wang, Pratik Chaudhari, Christos Davatzikos
Proceedings of the National Academy of Sciences (2023) Vol. 120, Iss. 6
Open Access | Times Cited: 44

Showing 1-25 of 44 citing articles:

Data leakage inflates prediction performance in connectome-based machine learning models
Matthew Rosenblatt, Link Tejavibulya, Rongtao Jiang, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 31
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: 22
A scoping review of fair machine learning techniques when using real-world data
Yu Huang, Jingchuan Guo, Wei‐Han Chen, et al.
Journal of Biomedical Informatics (2024) Vol. 151, pp. 104622-104622
Open Access | Times Cited: 16
Understanding Biases and Disparities in Radiology AI Datasets: A Review
Satvik Tripathi, K. R. Gabriel, Suhani Dheer, et al.
Journal of the American College of Radiology (2023) Vol. 20, Iss. 9, pp. 836-841
Closed Access | Times Cited: 27
Machine Learning and Bias in Medical Imaging: Opportunities and Challenges
Amey Vrudhula, Alan C. Kwan, David Ouyang, et al.
Circulation Cardiovascular Imaging (2024) Vol. 17, Iss. 2
Closed Access | Times Cited: 10
Annual Research Review: ‘There, the dance is – at the still point of the turning world’ – dynamic systems perspectives on coregulation and dysregulation during early development
Sam Wass, Emily Greenwood, Giovanni Esposito, et al.
Journal of Child Psychology and Psychiatry (2024) Vol. 65, Iss. 4, pp. 481-507
Open Access | Times Cited: 9
The future of machine learning for small-molecule drug discovery will be driven by data
G. J. DURANT, Fergus Boyles, Kristian Birchall, et al.
Nature Computational Science (2024) Vol. 4, Iss. 10, pp. 735-743
Closed Access | Times Cited: 5
Neuroimaging data repositories and AI-driven healthcare—Global aspirations vs. ethical considerations in machine learning models of neurological disease
Christine Lock, Nicole Si Min Tan, Ian James Long, et al.
Frontiers in Artificial Intelligence (2024) Vol. 6
Open Access | Times Cited: 4
Evaluating Machine Learning Stability in Predicting Depression and Anxiety Amidst Subjective Response Errors
Wai Lim Ku, Hua Min
Healthcare (2024) Vol. 12, Iss. 6, pp. 625-625
Open Access | Times Cited: 4
Advancing Fairness in Cardiac Care: Strategies for Mitigating Bias in Artificial Intelligence Models Within Cardiology
Alexis Nolin-Lapalme, Denis Corbin, Olivier Tastet, et al.
Canadian Journal of Cardiology (2024) Vol. 40, Iss. 10, pp. 1907-1921
Closed Access | Times Cited: 4
Critical evaluation of feature importance assessment in FFNN-based models for predicting Kamlet-Taft parameters
Yoshiyasu Takefuji
Green Chemical Engineering (2025)
Open Access
Bias and fairness
Andrew P. King, Tiarna Lee
Elsevier eBooks (2025), pp. 247-264
Closed Access
Prospective Validation and Implementation Pilot Study of an Emergency Department Heart Failure Risk Stratification Tool
Dana R. Sax, Jie Huang, Dustin G. Mark, et al.
JACC Heart Failure (2025)
Closed Access
Evidence-based personalised medicine in critical care: a framework for quantifying and applying individualised treatment effects in patients who are critically ill
Elizabeth Munroe, Alexandra B. Spicer, Andrea Castellví-Font, et al.
The Lancet Respiratory Medicine (2025)
Closed Access
Artificial intelligence for dementia prevention
Danielle Newby, Vasiliki Orgeta, Charles R. Marshall, et al.
Alzheimer s & Dementia (2023) Vol. 19, Iss. 12, pp. 5952-5969
Open Access | Times Cited: 10
Fit-For-Purpose Creativity Assessment: Automatic Scoring of the Test of Creative Thinking – Drawing Production (TCT-DP)
David H. Cropley, Caroline Theurer, A. C. Sven Mathijssen, et al.
Creativity Research Journal (2024), pp. 1-16
Open Access | Times Cited: 3
Addressing fairness issues in deep learning-based medical image analysis: a systematic review
Zikang Xu, Jun Li, Qingsong Yao, et al.
npj Digital Medicine (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 3
Methods and Annotated Data Sets Used to Predict the Gender and Age of Twitter Users: Scoping Review
Karen O’Connor, Su Golder, Davy Weissenbacher, et al.
Journal of Medical Internet Research (2024) Vol. 26, pp. e47923-e47923
Open Access | Times Cited: 2
Bias in context: What to do when complete bias removal is not an option
Sune Holm, Eike Petersen, Melanie Ganz, et al.
Proceedings of the National Academy of Sciences (2023) Vol. 120, Iss. 23
Open Access | Times Cited: 5
Physiological influences on neurovascular coupling: A systematic review of multimodal imaging approaches and recommendations for future study designs
Joel S. Burma, Damian M. Bailey, Nathan E. Johnson, et al.
Experimental Physiology (2024)
Open Access | Times Cited: 1
Quantifying the Impact of Population Shift Across Age and Sex for Abdominal Organ Segmentation
Kate Čevora, Ben Glocker, Wenjia Bai
Lecture notes in computer science (2024), pp. 88-97
Closed Access | Times Cited: 1
Deep Neural Networks-Based Age Estimation of Cadavers Using CT Imaging of Vertebrae
Hiroki Kondou, Rina Morohashi, Hiroaki Ichioka, et al.
International Journal of Environmental Research and Public Health (2023) Vol. 20, Iss. 6, pp. 4806-4806
Open Access | Times Cited: 3
Artificial Intelligence is Changing the Ethics of Medicine: Reflections from the Australian Epilepsy Project
Mangor Pedersen, Heath Pardoe, Anton de Weger, et al.
(2023)
Open Access | Times Cited: 3
Machine Learning Improves the Accuracy of Trauma Team Activation Level Assignments in Pediatric Patients
Catherine W. Liu, Miranda A. Chacon, Loralai Crawford, et al.
Journal of Pediatric Surgery (2023) Vol. 59, Iss. 1, pp. 74-79
Closed Access | Times Cited: 3
The effects of data leakage on connectome-based machine learning models
Matthew Rosenblatt, Link Tejavibulya, Rongtao Jiang, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 2
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