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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:

Predicting Response to Repetitive Transcranial Magnetic Stimulation in Patients With Schizophrenia Using Structural Magnetic Resonance Imaging: A Multisite Machine Learning Analysis
Nikolaos Koutsouleris, Thomas Wobrock, Birgit Guse, et al.
Schizophrenia Bulletin (2017) Vol. 44, Iss. 5, pp. 1021-1034
Open Access | Times Cited: 75

Showing 1-25 of 75 citing articles:

Evidence-based guidelines on the therapeutic use of repetitive transcranial magnetic stimulation (rTMS): An update (2014–2018)
Jean‐Pascal Lefaucheur, André Alemán, Chris Baeken, et al.
Clinical Neurophysiology (2020) Vol. 131, Iss. 2, pp. 474-528
Open Access | Times Cited: 1619
Machine learning in mental health: a scoping review of methods and applications
Adrian Shatte, Delyse Hutchinson, Samantha Teague
Psychological Medicine (2019) Vol. 49, Iss. 09, pp. 1426-1448
Open Access | Times Cited: 700
Implementing Precision Psychiatry: A Systematic Review of Individualized Prediction Models for Clinical Practice
Gonzalo Salazar de Pablo, Erich Studerus, Julio Vaquerizo‐Serrano, et al.
Schizophrenia Bulletin (2020) Vol. 47, Iss. 2, pp. 284-297
Open Access | Times Cited: 167
Making Individual Prognoses in Psychiatry Using Neuroimaging and Machine Learning
Ronald J. Janssen, Janaı́na Mourão-Miranda, Hugo G. Schnack
Biological Psychiatry Cognitive Neuroscience and Neuroimaging (2018) Vol. 3, Iss. 9, pp. 798-808
Open Access | Times Cited: 164
Methodological and Quality Flaws in the Use of Artificial Intelligence in Mental Health Research: Systematic Review
Roberto Tornero-Costa, Antonio Martínez-Millana, Natasha Azzopardi‐Muscat, et al.
JMIR Mental Health (2023) Vol. 10, pp. e42045-e42045
Open Access | Times Cited: 55
Deep learning and machine learning in psychiatry: a survey of current progress in depression detection, diagnosis and treatment
Matthew Squires, Xiaohui Tao, Soman Elangovan, et al.
Brain Informatics (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 51
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: 3
Improving Mental Health Services: A 50-Year Journey from Randomized Experiments to Artificial Intelligence and Precision Mental Health
Leonard Bickman
Administration and Policy in Mental Health and Mental Health Services Research (2020) Vol. 47, Iss. 5, pp. 795-843
Open Access | Times Cited: 137
Efficacy and Safety of Transcranial Direct Current Stimulation for Treating Negative Symptoms in Schizophrenia
Leandro Valiengo, Stephan Goerigk, Pedro Caldana Gordon, et al.
JAMA Psychiatry (2019) Vol. 77, Iss. 2, pp. 121-121
Open Access | Times Cited: 118
Ethical considerations for precision psychiatry: A roadmap for research and clinical practice
Paolo Fusar‐Poli, Mirko Manchia, Nikolaos Koutsouleris, et al.
European Neuropsychopharmacology (2022) Vol. 63, pp. 17-34
Open Access | Times Cited: 65
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
Recent advances in psychoradiology
Lekai Luo, Wanfang You, Melissa P. DelBello, et al.
Physics in Medicine and Biology (2022) Vol. 67, Iss. 23, pp. 23TR01-23TR01
Open Access | Times Cited: 50
Translational machine learning for psychiatric neuroimaging
Martin Walter, Sarah Alizadeh, Hamidreza Jamalabadi, et al.
Progress in Neuro-Psychopharmacology and Biological Psychiatry (2018) Vol. 91, pp. 113-121
Closed Access | Times Cited: 69
Developments in Biological Mechanisms and Treatments for Negative Symptoms and Cognitive Dysfunction of Schizophrenia
Qiongqiong Wu, Xiaoyi Wang, Ying Wang, et al.
Neuroscience Bulletin (2021) Vol. 37, Iss. 11, pp. 1609-1624
Open Access | Times Cited: 41
A Pattern of Cognitive Deficits Stratified for Genetic and Environmental Risk Reliably Classifies Patients With Schizophrenia From Healthy Control Subjects
Linda A. Antonucci, Giulio Pergola, Alessandro Pigoni, et al.
Biological Psychiatry (2019) Vol. 87, Iss. 8, pp. 697-707
Closed Access | Times Cited: 41
Forty years of structural brain imaging in mental disorders: is it clinically useful or not?
Peter Falkai, Andrea Schmitt, Nancy C. Andreasen
Dialogues in Clinical Neuroscience (2018) Vol. 20, Iss. 3, pp. 179-186
Open Access | Times Cited: 41
Prediction of early response to overall treatment for schizophrenia: A functional magnetic resonance imaging study
Long‐Biao Cui, Min Cai, Xing‐Rui Wang, et al.
Brain and Behavior (2019) Vol. 9, Iss. 2
Open Access | Times Cited: 39
Structural similarity networks predict clinical outcome in early-phase psychosis
Philipp Homan, Miklós Árgyelán, Pamela DeRosse, et al.
Neuropsychopharmacology (2019) Vol. 44, Iss. 5, pp. 915-922
Open Access | Times Cited: 38
The intervention, the patient and the illness – Personalizing non-invasive brain stimulation in psychiatry
Frank Padberg, Lucia Bulubas, Yuki Mizutani-Tiebel, et al.
Experimental Neurology (2021) Vol. 341, pp. 113713-113713
Open Access | Times Cited: 31
Multimodal workflows optimally predict response to repetitive transcranial magnetic stimulation in patients with schizophrenia: a multisite machine learning analysis
Mark Sen Dong, Jaroslav Rokicki, Dominic Dwyer, et al.
Translational Psychiatry (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 4
Sex Matters: A Multivariate Pattern Analysis of Sex- and Gender-Related Neuroanatomical Differences in Cis- and Transgender Individuals Using Structural Magnetic Resonance Imaging
P. Baldinger, Maria F Urquijo Castro, René Seiger, et al.
Cerebral Cortex (2019) Vol. 30, Iss. 3, pp. 1345-1356
Open Access | Times Cited: 35
Functional neuroimaging in treatment resistant schizophrenia: A systematic review
Cinzia Molent, Daniele Olivo, Robert Christian Wolf, et al.
Neuroscience & Biobehavioral Reviews (2019) Vol. 104, pp. 178-190
Closed Access | Times Cited: 30
Machine learning-based prediction of antipsychotic efficacy from brain gray matter structure in drug-naive first-episode schizophrenia
Xiaodong Guo, Enpeng Zhou, Xianghe Wang, et al.
Schizophrenia (2025) Vol. 11, Iss. 1
Open Access
Digital Twin Brain Predicts rTMS Effects on Brain State Dynamics in Chronic Tinnitus
Jiaqi Zhang, Shuting Han, Yongcong Shen, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2025)
Open Access
Brain connectomics markers for response prediction to transcranial magnetic stimulation in cocaine use disorder
Nayereh Ghazi, Eduardo A. Garza‐Villarreal, Hamid Soltanian‐Zadeh
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
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