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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:

Neuroimaging-based Individualized Prediction of Cognition and Behavior for Mental Disorders and Health: Methods and Promises
Jing Sui, Rongtao Jiang, Juan Bustillo, et al.
Biological Psychiatry (2020) Vol. 88, Iss. 11, pp. 818-828
Open Access | Times Cited: 267

Showing 1-25 of 267 citing articles:

Linking interindividual variability in brain structure to behaviour
Sarah Genon, Simon B. Eickhoff, Shahrzad Kharabian Masouleh
Nature reviews. Neuroscience (2022) Vol. 23, Iss. 5, pp. 307-318
Closed Access | Times Cited: 153
A Mutual Multi-Scale Triplet Graph Convolutional Network for Classification of Brain Disorders Using Functional or Structural Connectivity
Dongren Yao, Jing Sui, Mingliang Wang, et al.
IEEE Transactions on Medical Imaging (2021) Vol. 40, Iss. 4, pp. 1279-1289
Open Access | Times Cited: 111
Comparison of individualized behavioral predictions across anatomical, diffusion and functional connectivity MRI
Leon Qi Rong Ooi, Jianzhong Chen, Shaoshi Zhang, et al.
NeuroImage (2022) Vol. 263, pp. 119636-119636
Open Access | Times Cited: 83
Modern views of machine learning for precision psychiatry
Zhe Chen, Prathamesh Kulkarni, Isaac R. Galatzer‐Levy, et al.
Patterns (2022) Vol. 3, Iss. 11, pp. 100602-100602
Open Access | Times Cited: 83
Associations between grip strength, brain structure, and mental health in > 40,000 participants from the UK Biobank
Rongtao Jiang, Margaret L. Westwater, Stephanie Noble, et al.
BMC Medicine (2022) Vol. 20, Iss. 1
Open Access | Times Cited: 69
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
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: 30
CI-GNN: A Granger causality-inspired graph neural network for interpretable brain network-based psychiatric diagnosis
Kaizhong Zheng, Shujian Yu, Badong Chen
Neural Networks (2024) Vol. 172, pp. 106147-106147
Open Access | Times Cited: 23
Functional magnetic resonance imaging in schizophrenia: current evidence, methodological advances, limitations and future directions
Aristotle N. Voineskos, Colin Hawco, Nicholas H. Neufeld, et al.
World Psychiatry (2024) Vol. 23, Iss. 1, pp. 26-51
Open Access | Times Cited: 20
Advances in Neuroimaging and Deep Learning for Emotion Detection: A Systematic Review of Cognitive Neuroscience and Algorithmic Innovations
Constantinos Halkiopoulos, Evgenia Gkintoni, Anthimos Aroutzidis, et al.
Diagnostics (2025) Vol. 15, Iss. 4, pp. 456-456
Open Access | Times Cited: 3
From Serendipity to Precision: Integrating AI, Multi-Omics, and Human-Specific Models for Personalized Neuropsychiatric Care
Masaru Tanaka
Biomedicines (2025) Vol. 13, Iss. 1, pp. 167-167
Open Access | Times Cited: 1
What have we really learned from functional connectivity in clinical populations?
Jiahe Zhang, Aaron Kucyi, Jovicarole Raya, et al.
NeuroImage (2021) Vol. 242, pp. 118466-118466
Open Access | Times Cited: 100
Machine learning prediction of cognition from functional connectivity: Are feature weights reliable?
Ye Tian, Andrew Zalesky
NeuroImage (2021) Vol. 245, pp. 118648-118648
Open Access | Times Cited: 88
Effect sizes of associations between neuroimaging measures and affective symptoms: A meta‐analysis
Chunliang Feng, Wesley K. Thompson, Martin P. Paulus
Depression and Anxiety (2021) Vol. 39, Iss. 1, pp. 19-25
Open Access | Times Cited: 82
Beyond fingerprinting: Choosing predictive connectomes over reliable connectomes
Emily S. Finn, Monica D. Rosenberg
NeuroImage (2021) Vol. 239, pp. 118254-118254
Open Access | Times Cited: 78
Integrating across neuroimaging modalities boosts prediction accuracy of cognitive ability
Javier Rasero, Amy Isabella Sentis, Fang‐Cheng Yeh, et al.
PLoS Computational Biology (2021) Vol. 17, Iss. 3, pp. e1008347-e1008347
Open Access | Times Cited: 60
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: 60
Super-Recognizers – a novel diagnostic framework, 70 cases, and guidelines for future work
Meike Ramon
Neuropsychologia (2021) Vol. 158, pp. 107809-107809
Open Access | Times Cited: 56
On the prediction of human intelligence from neuroimaging: A systematic review of methods and reporting
Bruno Hebling Vieira, Gustavo Santo Pedro Pamplona, Karim Fachinello, et al.
Intelligence (2022) Vol. 93, pp. 101654-101654
Open Access | Times Cited: 47
A Neuroimaging Signature of Cognitive Aging from Whole‐Brain Functional Connectivity
Rongtao Jiang, Dustin Scheinost, Nianming Zuo, et al.
Advanced Science (2022) Vol. 9, Iss. 24
Open Access | Times Cited: 41
Precision dynamical mapping using topological data analysis reveals a hub-like transition state at rest
Manish Saggar, James M. Shine, Raphaël Liégeois, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 39
Predicting the future of neuroimaging predictive models in mental health
Link Tejavibulya, Max Rolison, Siyuan Gao, et al.
Molecular Psychiatry (2022) Vol. 27, Iss. 8, pp. 3129-3137
Open Access | Times Cited: 38
Transdiagnostic Connectome-Based Prediction of Craving
Kathleen A. Garrison, Rajita Sinha, Marc N. Potenza, et al.
American Journal of Psychiatry (2023) Vol. 180, Iss. 6, pp. 445-453
Open Access | Times Cited: 37
Machine learning and artificial intelligence in neuroscience: A primer for researchers
Fakhirah Badrulhisham, Esther Pogatzki‐Zahn, Daniel Segelcke, et al.
Brain Behavior and Immunity (2023) Vol. 115, pp. 470-479
Open Access | Times Cited: 36
Reply to: Multivariate BWAS can be replicable with moderate sample sizes
Brenden Tervo‐Clemmens, Scott Marek, Roselyne J. Chauvin, et al.
Nature (2023) Vol. 615, Iss. 7951, pp. E8-E12
Open Access | Times Cited: 30
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