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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:

Magnetic resonance imaging for individual prediction of treatment response in major depressive disorder: a systematic review and meta-analysis
Sem E Cohen, Jasper B. Zantvoord, Babet N. Wezenberg, et al.
Translational Psychiatry (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 55

Showing 1-25 of 55 citing articles:

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
Systematic review and meta-analysis of performance of wearable artificial intelligence in detecting and predicting depression
Alaa Abd‐Alrazaq, Rawan AlSaad, Farag Shuweihdi, et al.
npj Digital Medicine (2023) Vol. 6, Iss. 1
Open Access | Times Cited: 46
AI-assisted prediction of differential response to antidepressant classes using electronic health records
Yi-han Sheu, Colin Magdamo, Matthew Miller, et al.
npj Digital Medicine (2023) Vol. 6, Iss. 1
Open Access | Times Cited: 44
Treatment Response Prediction in Major Depressive Disorder Using Multimodal MRI and Clinical Data: Secondary Analysis of a Randomized Clinical Trial
Maarten G. Poirot, Henricus G. Ruhé, Henk J. M. M. Mutsaerts, et al.
American Journal of Psychiatry (2024) Vol. 181, Iss. 3, pp. 223-233
Open Access | Times Cited: 18
Predicting treatment outcomes in major depressive disorder using brain magnetic resonance imaging: a meta-analysis
Fenghua Long, Yufei Chen, Qian Zhang, et al.
Molecular Psychiatry (2024)
Closed Access | Times Cited: 17
Predicting treatment response using EEG in major depressive disorder: A machine-learning meta-analysis
Devon Watts, Rafaela Fernandes Pulice, J.P. Reilly, et al.
Translational Psychiatry (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 60
Can we predict who will benefit from cognitive-behavioural therapy? A systematic review and meta-analysis of machine learning studies
Sandra Vieira, Xinyi Liang, Raquel Guiomar, et al.
Clinical Psychology Review (2022) Vol. 97, pp. 102193-102193
Open Access | Times Cited: 47
Evaluating Robustness of Brain Stimulation Biomarkers for Depression: A Systematic Review of Magnetic Resonance Imaging and Electroencephalography Studies
Debby Klooster, Helena Voetterl, Chris Baeken, et al.
Biological Psychiatry (2023) Vol. 95, Iss. 6, pp. 553-563
Open Access | Times Cited: 27
The power of many brains: Catalyzing neuropsychiatric discovery through open neuroimaging data and large-scale collaboration
Bin Lü, Xiao Chen, F. Xavier Castellanos, et al.
Science Bulletin (2024) Vol. 69, Iss. 10, pp. 1536-1555
Open Access | Times Cited: 9
Stratified psychiatry: Tomorrow's precision psychiatry?
Martijn Arns, Hanneke van Dijk, Jurjen J. Luykx, et al.
European Neuropsychopharmacology (2021) Vol. 55, pp. 14-19
Open Access | Times Cited: 55
Psychiatry in the Digital Age: A Blessing or a Curse?
Carl B. Roth, Andreas Papassotiropoulos, Annette Beatrix Brühl, et al.
International Journal of Environmental Research and Public Health (2021) Vol. 18, Iss. 16, pp. 8302-8302
Open Access | Times Cited: 46
The Association between Vegan, Vegetarian, and Omnivore Diet Quality and Depressive Symptoms in Adults: A Cross-Sectional Study
Hayley Walsh, Megan Lee, Talitha Best
International Journal of Environmental Research and Public Health (2023) Vol. 20, Iss. 4, pp. 3258-3258
Open Access | Times Cited: 17
Mood Disorder Severity and Subtype Classification Using Multimodal Deep Neural Network Models
Joo Hun Yoo, Harim Jeong, Ji Hyun An, et al.
Sensors (2024) Vol. 24, Iss. 2, pp. 715-715
Open Access | Times Cited: 5
Predicting Antidepressant Treatment Response From Cortical Structure on MRI: A Mega‐Analysis From the ENIGMA‐MDD Working Group
Maarten G. Poirot, Daphne E. Boucherie, Matthan W.A. Caan, et al.
Human Brain Mapping (2025) Vol. 46, Iss. 1
Open Access
Neuroimaging and Circuit Mechanisms of Depression
Adrienne L. Romer, Michele A. Bertocci, Mary L. Phillips, et al.
Oxford University Press eBooks (2025), pp. 375-392
Closed Access
Generalizability of clinical prediction models in mental health
Maike Richter, Daniel Emden, Ramona Leenings, et al.
Molecular Psychiatry (2025)
Open Access
Prediction of remission among patients with a major depressive disorder based on the resting-state functional connectivity of emotion regulation networks
Hang Wu, Rui Liu, Jingjing Zhou, et al.
Translational Psychiatry (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 21
Predicting treatment outcome based on resting-state functional connectivity in internalizing mental disorders: A systematic review and meta-analysis
Charlotte Meinke, Ulrike Lueken, Henrik Walter, et al.
Neuroscience & Biobehavioral Reviews (2024) Vol. 160, pp. 105640-105640
Open Access | Times Cited: 4
Prediction models for treatment response in migraine: a systematic review and meta-analysis
Qiuyi Chen, Junrong Zhang, Binghao Cao, et al.
The Journal of Headache and Pain (2025) Vol. 26, Iss. 1
Open Access
Increased thalamic gray matter volume induced by repetitive transcranial magnetic stimulation treatment in patients with major depressive disorder
Zhongheng Wang, Dongning Zhang, Muzhen Guan, et al.
Frontiers in Psychiatry (2023) Vol. 14
Open Access | Times Cited: 10
Development and validation of a multimodal neuroimaging biomarker for electroconvulsive therapy outcome in depression: a multicenter machine learning analysis
Willem B. Bruin, Leif Oltedal, Hauke Bartsch, et al.
Psychological Medicine (2023) Vol. 54, Iss. 3, pp. 495-506
Open Access | Times Cited: 10
Sequence Modeling of Passive Sensing Data for Treatment Response Prediction in Major Depressive Disorder
Bochao Zou, Xiaolong Zhang, Le Xiao, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2023) Vol. 31, pp. 1786-1795
Open Access | Times Cited: 9
White matter integrity and medication response to antidepressants in major depressive disorder: a review of the literature
Giovanni Videtta, Letizia Squarcina, Cecilia Prunas, et al.
Frontiers in Psychiatry (2024) Vol. 14
Open Access | Times Cited: 3
Neurophysiological and neuroimaging markers of repetitive transcranial magnetic stimulation treatment response in major depressive disorder: A systematic review and meta-analysis of predictive modeling studies
Min Xia Jin, Penny Ping Qin, Adam W.L. Xia, et al.
Neuroscience & Biobehavioral Reviews (2024) Vol. 162, pp. 105695-105695
Closed Access | Times Cited: 3
Breakthroughs and challenges for generating brain network-based biomarkers of treatment response in depression
Sapolnach Prompiengchai, Katharine Dunlop
Neuropsychopharmacology (2024) Vol. 50, Iss. 1, pp. 230-245
Closed Access | Times Cited: 3
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