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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:

Predictive analytics in mental health: applications, guidelines, challenges and perspectives
Tim Hahn, Andrew A. Nierenberg, Susan Whitfield‐Gabrieli
Molecular Psychiatry (2016) Vol. 22, Iss. 1, pp. 37-43
Closed Access | Times Cited: 115

Showing 26-50 of 115 citing articles:

Predicting the 9-year course of mood and anxiety disorders with automated machine learning: A comparison between auto-sklearn, naïve Bayes classifier, and traditional logistic regression
Wessel A. van Eeden, Chuan Luo, Albert M. van Hemert, et al.
Psychiatry Research (2021) Vol. 299, pp. 113823-113823
Open Access | Times Cited: 39
Confound Removal and Normalization in Practice: A Neuroimaging Based Sex Prediction Case Study
Shammi More, Simon B. Eickhoff, Julian Caspers, et al.
Lecture notes in computer science (2021), pp. 3-18
Open Access | Times Cited: 37
NeuroBlu, an electronic health record (EHR) trusted research environment (TRE) to support mental healthcare analytics with real-world data
Rashmi Patel, Soon Nan Wee, Rajagopalan Ramaswamy, et al.
BMJ Open (2022) Vol. 12, Iss. 4, pp. e057227-e057227
Open Access | Times Cited: 23
Application of machine learning techniques in the diagnostic approach of PTSD using MRI neuroimaging data: A systematic review
Yingjie Jia, Bo Yang, Yi‐Hsin Yang, et al.
Heliyon (2024) Vol. 10, Iss. 7, pp. e28559-e28559
Open Access | Times Cited: 5
Precision pharmacotherapy: psychiatry’s future direction in preventing, diagnosing, and treating mental disorders
Andreas Menke
Pharmacogenomics and Personalized Medicine (2018) Vol. Volume 11, pp. 211-222
Open Access | Times Cited: 39
Predictors of remission from body dysmorphic disorder after internet-delivered cognitive behavior therapy: a machine learning approach
Oskar Flygare, Jesper Enander, Erik Andersson, et al.
BMC Psychiatry (2020) Vol. 20, Iss. 1
Open Access | Times Cited: 37
NEW INSIGHTS INTO SCHIZOPHRENIA: A LOOK AT THE EYE AND RELATED STRUCTURES
Darija Jurišić, Ivan Ćavar, Antonio Sesar, et al.
Psychiatria Danubina (2020) Vol. 32, Iss. 1, pp. 60-69
Open Access | Times Cited: 36
The peripartum human brain: Current understanding and future perspectives
Julia Sacher, Natalia Chechko, Udo Dannlowski, et al.
Frontiers in Neuroendocrinology (2020) Vol. 59, pp. 100859-100859
Closed Access | Times Cited: 33
Mental Health in Tech: Analysis of Workplace Risk Factors and Impact of COVID-19
K. M. Mitravinda, Devika Nair, Gowri Srinivasa
SN Computer Science (2023) Vol. 4, Iss. 2
Open Access | Times Cited: 13
PredPsych: A toolbox for predictive machine learning-based approach in experimental psychology research
Atesh Koul, Cristina Becchio, Andrea Cavallo
Behavior Research Methods (2017) Vol. 50, Iss. 4, pp. 1657-1672
Open Access | Times Cited: 35
Bridging the Gaps Between Basic Science and Cognitive-Behavioral Treatments for Anxiety Disorders in Routine Care
Jan Richter, Andre Pittig, Maike Hollandt, et al.
Zeitschrift für Psychologie (2017) Vol. 225, Iss. 3, pp. 252-267
Closed Access | Times Cited: 35
Artificial intelligence and counseling: Four levels of implementation
Russell Fulmer
Theory & Psychology (2019) Vol. 29, Iss. 6, pp. 807-819
Closed Access | Times Cited: 34
Theranostic markers for personalized therapy of spider phobia: Methods of a bicentric external cross‐validation machine learning approach
Hanna Schwarzmeier, Elisabeth J. Leehr, Joscha Böhnlein, et al.
International Journal of Methods in Psychiatric Research (2019) Vol. 29, Iss. 2
Open Access | Times Cited: 31
Predicting the naturalistic course in anxiety disorders using clinical and biological markers: a machine learning approach
Wicher A. Bokma, Paul Zhutovsky, Erik J. Giltay, et al.
Psychological Medicine (2020) Vol. 52, Iss. 1, pp. 57-67
Open Access | Times Cited: 28
Machine learning-based prediction of illness course in major depression: The relevance of risk factors
Lea Teutenberg, Frederike Stein, Florian Thomas‐Odenthal, et al.
Journal of Affective Disorders (2025)
Closed Access
The balance and integration of artificial intelligence within cognitive behavioral therapy interventions
Jennifer Mize Nelson, J. Martin Kaplan, Gabriel Simerly, et al.
Current Psychology (2025)
Closed Access
Development of a machine learning-based multivariable prediction model for the naturalistic course of generalized anxiety disorder
Candice Basterfield, Michelle G. Newman
Journal of Anxiety Disorders (2025), pp. 102978-102978
Closed Access
Design and methods of the research unit 5187 PREACT (towards precision psychotherapy for non-respondent patients: from signatures to predictions to clinical utility) – a study protocol for a multicentre observational study in outpatient clinics
Till Langhammer, Chantal Unterfeld, Felix Blankenburg, et al.
BMJ Open (2025) Vol. 15, Iss. 2, pp. e094110-e094110
Open Access
Using machine learning methods to predict the outcome of psychological therapies for post-traumatic stress disorder: A systematic review
James Tait, Stephen Kellett, Jaime Delgadillo
Journal of Anxiety Disorders (2025), pp. 103003-103003
Closed Access
Bridging Technical and Clinical needs: A Case Study on Developing a Suicide Risk Prediction Algorithm Using EHR-data in Real-World Mental Health Care (Preprint)
L. Markl Hummel, Karin Lorenz-Artz, Joyce Bierbooms, et al.
(2025)
Closed Access
MRI-derived estimation of biological aging in patients with affective disorders in a 9-year follow-up - a prospective marker of future recurrence
Katharina Förster, Nils R. Winter, Jan Ernsting, et al.
medRxiv (Cold Spring Harbor Laboratory) (2025)
Open Access
Aifred Health, a Deep Learning Powered Clinical Decision Support System for Mental Health
David Benrimoh, Robert Fratila, Sonia Israel, et al.
˜The œSpringer series on challenges in machine learning (2018), pp. 251-287
Closed Access | Times Cited: 30
Predicting depressed and elevated mood symptomatology in bipolar disorder using brain functional connectomes
Anjali Sankar, Xilin Shen, Lejla Čolić, et al.
Psychological Medicine (2023) Vol. 53, Iss. 14, pp. 6656-6665
Open Access | Times Cited: 9
Do Statins Have Antidepressant Effects?
Ole Köhler‐Forsberg, Christiane Gasse, Michael Berk, et al.
CNS Drugs (2017) Vol. 31, Iss. 5, pp. 335-343
Closed Access | Times Cited: 27
Clinically useful brain imaging for neuropsychiatry: How can we get there?
Michael P. Milham, R. Cameron Craddock, Arno Klein
Depression and Anxiety (2017) Vol. 34, Iss. 7, pp. 578-587
Open Access | Times Cited: 27

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