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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:

Quantifying performance of machine learning methods for neuroimaging data
Lee Jollans, Rory Boyle, Éric Artiges, et al.
NeuroImage (2019) Vol. 199, pp. 351-365
Open Access | Times Cited: 156

Showing 1-25 of 156 citing articles:

Accurate brain age prediction with lightweight deep neural networks
Han Peng, Weikang Gong, Christian F. Beckmann, et al.
Medical Image Analysis (2020) Vol. 68, pp. 101871-101871
Open Access | Times Cited: 369
Deep learning encodes robust discriminative neuroimaging representations to outperform standard machine learning
Anees Abrol, Zening Fu, Mustafa S. Salman, et al.
Nature Communications (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 161
A downscaling approach for constructing high-resolution precipitation dataset over the Tibetan Plateau from ERA5 reanalysis
Yaozhi Jiang, Kun Yang, Changkun Shao, et al.
Atmospheric Research (2021) Vol. 256, pp. 105574-105574
Closed Access | Times Cited: 115
Mind the gap: Performance metric evaluation in brain‐age prediction
Ann‐Marie G. de Lange, Melis Anatürk, Jaroslav Rokicki, et al.
Human Brain Mapping (2022) Vol. 43, Iss. 10, pp. 3113-3129
Open Access | Times Cited: 99
The Burden of Reliability: How Measurement Noise Limits Brain-Behaviour Predictions
Martin Gell, Simon B. Eickhoff, Amir Omidvarnia, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 43
Can artificial intelligence be the future solution to the enormous challenges and suffering caused by Schizophrenia?
Shijie Jiang, Qiyu Jia, Zhenlei Peng, et al.
Schizophrenia (2025) Vol. 11, Iss. 1
Open Access | Times Cited: 2
Brain-predicted age difference score is related to specific cognitive functions: a multi-site replication analysis
Rory Boyle, Lee Jollans, Laura M. Rueda‐Delgado, et al.
Brain Imaging and Behavior (2020) Vol. 15, Iss. 1, pp. 327-345
Open Access | Times Cited: 99
Machine Learning Methods for Diagnosing Autism Spectrum Disorder and Attention- Deficit/Hyperactivity Disorder Using Functional and Structural MRI: A Survey
Taban Eslami, Fahad Almuqhim, Joseph S. Raiker, et al.
Frontiers in Neuroinformatics (2021) Vol. 14
Open Access | Times Cited: 85
A comparison of resting state EEG and structural MRI for classifying Alzheimer’s disease and mild cognitive impairment
Francesca R Farina, Derya Durusu Emek‐Savaş, Laura M. Rueda‐Delgado, et al.
NeuroImage (2020) Vol. 215, pp. 116795-116795
Open Access | Times Cited: 75
One Size Does Not Fit All: Methodological Considerations for Brain-Based Predictive Modeling in Psychiatry
Elvisha Dhamala, B.T. Thomas Yeo, Avram J. Holmes
Biological Psychiatry (2022) Vol. 93, Iss. 8, pp. 717-728
Closed Access | Times Cited: 61
Not just “big” data: Importance of sample size, measurement error, and uninformative predictors for developing prognostic models for digital interventions
Mary McNamara, Mackenzie Zisser, Christopher G. Beevers, et al.
Behaviour Research and Therapy (2022) Vol. 153, pp. 104086-104086
Open Access | Times Cited: 39
Deep Learning in Large and Multi-Site Structural Brain MR Imaging Datasets
Mariana Bento, Irene Fantini, Justin Park, et al.
Frontiers in Neuroinformatics (2022) Vol. 15
Open Access | Times Cited: 38
Toward Addiction Prediction: An Overview of Cross-Validated Predictive Modeling Findings and Considerations for Future Neuroimaging Research
Sarah W. Yip, Brian D. Kiluk, Dustin Scheinost
Biological Psychiatry Cognitive Neuroscience and Neuroimaging (2019) Vol. 5, Iss. 8, pp. 748-758
Open Access | Times Cited: 65
Modelling prognostic trajectories of cognitive decline due to Alzheimer's disease
Joseph Giorgio, Susan Landau, William J. Jagust, et al.
NeuroImage Clinical (2020) Vol. 26, pp. 102199-102199
Open Access | Times Cited: 61
Boost in Test–Retest Reliability in Resting State fMRI with Predictive Modeling
Aman Taxali, Mike Angstadt, Saige Rutherford, et al.
Cerebral Cortex (2020) Vol. 31, Iss. 6, pp. 2822-2833
Open Access | Times Cited: 61
Promising vulnerability markers of substance use and misuse: A review of human neurobehavioral studies
Briana Lees, Alexis García, Jennifer Debenham, et al.
Neuropharmacology (2021) Vol. 187, pp. 108500-108500
Open Access | Times Cited: 51
Promises and pitfalls of deep neural networks in neuroimaging-based psychiatric research
Fabian Eitel, Marc‐Andre Schulz, Moritz Seiler, et al.
Experimental Neurology (2021) Vol. 339, pp. 113608-113608
Open Access | Times Cited: 43
Machine learning algorithm selection for windage alteration fault diagnosis of mine ventilation system
Yuguo Li, Jian Liu, Qichao Zhou, et al.
Advanced Engineering Informatics (2022) Vol. 53, pp. 101666-101666
Closed Access | Times Cited: 36
Evaluation of Risk of Bias in Neuroimaging-Based Artificial Intelligence Models for Psychiatric Diagnosis
Zhiyi Chen, Xuerong Liu, Qingwu Yang, et al.
JAMA Network Open (2023) Vol. 6, Iss. 3, pp. e231671-e231671
Open Access | Times Cited: 19
Polyneuro risk scores capture widely distributed connectivity patterns of cognition
Nora Byington, Gracie Grimsrud, Michael A. Mooney, et al.
Developmental Cognitive Neuroscience (2023) Vol. 60, pp. 101231-101231
Open Access | Times Cited: 19
MLATE: Machine learning for predicting cell behavior on cardiac tissue engineering scaffolds
Saeed Rafieyan, Ebrahim Vasheghani‐Farahani, Nafiseh Baheiraei, et al.
Computers in Biology and Medicine (2023) Vol. 158, pp. 106804-106804
Closed Access | Times Cited: 19
The biological classification of mental disorders (BeCOME) study: a protocol for an observational deep-phenotyping study for the identification of biological subtypes
Tanja Brückl, Victor I. Spoormaker, Philipp G. Sämann, et al.
BMC Psychiatry (2020) Vol. 20, Iss. 1
Open Access | Times Cited: 48
Individual Differences in Cognitive Performance Are Better Predicted by Global Rather Than Localized BOLD Activity Patterns Across the Cortex
Weiqi Zhao, Clare E. Palmer, Wesley K. Thompson, et al.
Cerebral Cortex (2020) Vol. 31, Iss. 3, pp. 1478-1488
Open Access | Times Cited: 41
Volume of β-Bursts, But Not Their Rate, Predicts Successful Response Inhibition
Nadja Enz, Kathy Ruddy, Laura M. Rueda‐Delgado, et al.
Journal of Neuroscience (2021) Vol. 41, Iss. 23, pp. 5069-5079
Open Access | Times Cited: 38
Multimethod investigation of the neurobiological basis of ADHD symptomatology in children aged 9-10: baseline data from the ABCD study
Max M. Owens, Nicholas Allgaier, Sage Hahn, et al.
Translational Psychiatry (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 36
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