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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:

Testing a machine-learning algorithm to predict the persistence and severity of major depressive disorder from baseline self-reports
Ronald C. Kessler, Hanna M. van Loo, Klaas J. Wardenaar, et al.
Molecular Psychiatry (2016) Vol. 21, Iss. 10, pp. 1366-1371
Open Access | Times Cited: 211

Showing 1-25 of 211 citing articles:

Machine Learning Approaches for Clinical Psychology and Psychiatry
Dominic Dwyer, Peter Falkai, Nikolaos Koutsouleris
Annual Review of Clinical Psychology (2018) Vol. 14, Iss. 1, pp. 91-118
Closed Access | Times Cited: 754
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: 692
Treatment Selection in Depression
Zachary D. Cohen, Robert J. DeRubeis
Annual Review of Clinical Psychology (2018) Vol. 14, Iss. 1, pp. 209-236
Open Access | Times Cited: 394
Applications of machine learning algorithms to predict therapeutic outcomes in depression: A meta-analysis and systematic review
Yena Lee, Renee‐Marie Ragguett, Rodrigo B. Mansur, et al.
Journal of Affective Disorders (2018) Vol. 241, pp. 519-532
Closed Access | Times Cited: 353
The promise of machine learning in predicting treatment outcomes in psychiatry
Adam M. Chekroud, Julia Bondar, Jaime Delgadillo, et al.
World Psychiatry (2021) Vol. 20, Iss. 2, pp. 154-170
Open Access | Times Cited: 341
Prediction Models of Functional Outcomes for Individuals in the Clinical High-Risk State for Psychosis or With Recent-Onset Depression
Nikolaos Koutsouleris, Lana Kambeitz‐Ilankovic, Stephan Ruhrmann, et al.
JAMA Psychiatry (2018) Vol. 75, Iss. 11, pp. 1156-1156
Open Access | Times Cited: 292
Machine Learning in Healthcare
Hafsa Habehh, Suril Gohel
Current Genomics (2021) Vol. 22, Iss. 4, pp. 291-300
Open Access | Times Cited: 261
Prevention of Mental Health Disorders Using Internet- and Mobile-Based Interventions: A Narrative Review and Recommendations for Future Research
David Daniel Ebert, Pim Cuijpers, Ricardo F. Muñoz, et al.
Frontiers in Psychiatry (2017) Vol. 8
Open Access | Times Cited: 234
Predicting suicide attempts in adolescents with longitudinal clinical data and machine learning
Colin G. Walsh, Jessica D. Ribeiro, Joseph C. Franklin
Journal of Child Psychology and Psychiatry (2018) Vol. 59, Iss. 12, pp. 1261-1270
Closed Access | Times Cited: 219
Behavioral Modeling for Mental Health using Machine Learning Algorithms
M S Srividya, S. Mohanavalli, N. Bhalaji
Journal of Medical Systems (2018) Vol. 42, Iss. 5
Closed Access | Times Cited: 208
Problematic internet use as an age-related multifaceted problem: Evidence from a two-site survey
Konstantinos Ioannidis, Matthias S. Treder, Samuel R. Chamberlain, et al.
Addictive Behaviors (2018) Vol. 81, pp. 157-166
Open Access | Times Cited: 181
Using patient self-reports to study heterogeneity of treatment effects in major depressive disorder
Ronald C. Kessler, Hanna M. van Loo, Klaas J. Wardenaar, et al.
Epidemiology and Psychiatric Sciences (2016) Vol. 26, Iss. 1, pp. 22-36
Open Access | Times Cited: 170
The Science of Prognosis in Psychiatry
Paolo Fusar‐Poli, Ziad Hijazi, Daniel Ståhl, et al.
JAMA Psychiatry (2018) Vol. 75, Iss. 12, pp. 1289-1289
Closed Access | Times Cited: 170
Artificial Intelligence and Suicide Prevention: A Systematic Review of Machine Learning Investigations
Rebecca A. Bernert, Amanda Hilberg, Ruth Melia, et al.
International Journal of Environmental Research and Public Health (2020) Vol. 17, Iss. 16, pp. 5929-5929
Open Access | Times Cited: 162
The AURORA Study: a longitudinal, multimodal library of brain biology and function after traumatic stress exposure
Samuel A. McLean, Kerry J. Ressler, Karestan C. Koenen, et al.
Molecular Psychiatry (2019) Vol. 25, Iss. 2, pp. 283-296
Open Access | Times Cited: 151
Interpretable filter based convolutional neural network (IF-CNN) for glucose prediction and classification using PD-SS algorithm
R. Kamalraj, S. Neelakandan, Ranjith Kumar Manoharan, et al.
Measurement (2021) Vol. 183, pp. 109804-109804
Closed Access | Times Cited: 110
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
A Comparison of a Machine Learning Model with EuroSCORE II in Predicting Mortality after Elective Cardiac Surgery: A Decision Curve Analysis
Jérôme Allyn, Nicolas Allou, Pascal Augustin, et al.
PLoS ONE (2017) Vol. 12, Iss. 1, pp. e0169772-e0169772
Open Access | Times Cited: 166
Dynamic functional connectivity during task performance and rest predicts individual differences in attention across studies
Angus Ho Ching Fong, Kwangsun Yoo, Monica D. Rosenberg, et al.
NeuroImage (2018) Vol. 188, pp. 14-25
Open Access | Times Cited: 156
Prediction of major depressive disorder onset in college students
David Daniel Ebert, Claudia Buntrock, Philippe Mortier, et al.
Depression and Anxiety (2018) Vol. 36, Iss. 4, pp. 294-304
Open Access | Times Cited: 131
Clinical factors predicting treatment resistant depression: affirmative results from the European multicenter study
Alexander Kautzky, Markus Dold, Lucie Bartova, et al.
Acta Psychiatrica Scandinavica (2018) Vol. 139, Iss. 1, pp. 78-88
Open Access | Times Cited: 121
Results of the European Group for the Study of Resistant Depression (GSRD) — basis for further research and clinical practice
Lucie Bartova, Markus Dold, Alexander Kautzky, et al.
The World Journal of Biological Psychiatry (2019) Vol. 20, Iss. 6, pp. 427-448
Closed Access | Times Cited: 115
Novel Electronics for Flexible and Neuromorphic Computing
Han Eol Lee, Jung Hwan Park, Taejin Kim, et al.
Advanced Functional Materials (2018) Vol. 28, Iss. 32
Closed Access | Times Cited: 114
Predicting the naturalistic course of depression from a wide range of clinical, psychological, and biological data: a machine learning approach
Richard Dinga, André F. Marquand, Dick J. Veltman, et al.
Translational Psychiatry (2018) Vol. 8, Iss. 1
Open Access | Times Cited: 107
What big data can do for treatment in psychiatry
Claire M. Gillan, Robert Whelan
Current Opinion in Behavioral Sciences (2017) Vol. 18, pp. 34-42
Closed Access | Times Cited: 103
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