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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:

Cross-trial prediction of treatment outcome in depression: a machine learning approach
Adam M. Chekroud, Ryan Zotti, Zarrar Shehzad, et al.
The Lancet Psychiatry (2016) Vol. 3, Iss. 3, pp. 243-250
Closed Access | Times Cited: 579

Showing 1-25 of 579 citing articles:

High-performance medicine: the convergence of human and artificial intelligence
Eric J. Topol
Nature Medicine (2018) Vol. 25, Iss. 1, pp. 44-56
Closed Access | Times Cited: 4836
Computational psychiatry as a bridge from neuroscience to clinical applications
Quentin J. M. Huys, Tiago V. Maia, Michael J. Frank
Nature Neuroscience (2016) Vol. 19, Iss. 3, pp. 404-413
Open Access | Times Cited: 917
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: 741
Establishment of Best Practices for Evidence for Prediction
Russell A. Poldrack, Grace Huckins, Gaël Varoquaux
JAMA Psychiatry (2019) Vol. 77, Iss. 5, pp. 534-534
Open Access | Times Cited: 614
Artificial Intelligence for Mental Health and Mental Illnesses: an Overview
Sarah Graham, Colin A. Depp, Ellen Lee, et al.
Current Psychiatry Reports (2019) Vol. 21, Iss. 11
Open Access | Times Cited: 598
The 52 symptoms of major depression: Lack of content overlap among seven common depression scales
Eiko I. Fried
Journal of Affective Disorders (2016) Vol. 208, pp. 191-197
Closed Access | Times Cited: 538
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: 390
The Heterogeneity Problem: Approaches to Identify Psychiatric Subtypes
Eric Feczko, Óscar Miranda-Domínguez, Mollie Marr, et al.
Trends in Cognitive Sciences (2019) Vol. 23, Iss. 7, pp. 584-601
Open Access | Times Cited: 366
The WPA- Lancet Psychiatry Commission on the Future of Psychiatry
Dinesh Bhugra, Allan Tasman, Soumitra Pathare, et al.
The Lancet Psychiatry (2017) Vol. 4, Iss. 10, pp. 775-818
Open Access | Times Cited: 364
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: 350
Automated assessment of psychiatric disorders using speech: A systematic review
Daniel M. Low, Kate H. Bentley, Satrajit Ghosh
Laryngoscope Investigative Otolaryngology (2020) Vol. 5, Iss. 1, pp. 96-116
Open Access | Times Cited: 337
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: 329
The clinical characterization of the adult patient with depression aimed at personalization of management
Mario Maj, Dan J. Stein, Gordon Parker, et al.
World Psychiatry (2020) Vol. 19, Iss. 3, pp. 269-293
Open Access | Times Cited: 294
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
Artificial Intelligence and the Implementation Challenge
James Shaw, Frank Rudzicz, Trevor Jamieson, et al.
Journal of Medical Internet Research (2019) Vol. 21, Iss. 7, pp. e13659-e13659
Open Access | Times Cited: 285
AI in Health: State of the Art, Challenges, and Future Directions
Fei Wang, Anita M. Preininger
Yearbook of Medical Informatics (2019) Vol. 28, Iss. 01, pp. 016-026
Open Access | Times Cited: 279
Artificial intelligence and machine learning‐aided drug discovery in central nervous system diseases: State‐of‐the‐arts and future directions
Sezen Vatansever, Avner Schlessinger, Daniel Wacker, et al.
Medicinal Research Reviews (2020) Vol. 41, Iss. 3, pp. 1427-1473
Open Access | Times Cited: 263
Artificial Intelligence for Mental Health Care: Clinical Applications, Barriers, Facilitators, and Artificial Wisdom
Ellen Lee, John Torous, Munmun De Choudhury, et al.
Biological Psychiatry Cognitive Neuroscience and Neuroimaging (2021) Vol. 6, Iss. 9, pp. 856-864
Open Access | Times Cited: 239
Reevaluating the Efficacy and Predictability of Antidepressant Treatments
Adam M. Chekroud, Ralitza Gueorguieva, Harlan M. Krumholz, et al.
JAMA Psychiatry (2017) Vol. 74, Iss. 4, pp. 370-370
Open Access | Times Cited: 236
Internet-Based Cognitive-Behavioral Therapy for Depression: Current Progress and Future Directions
Christian A. Webb, Isabelle M. Rosso, Scott L. Rauch
Harvard Review of Psychiatry (2017) Vol. 25, Iss. 3, pp. 114-122
Open Access | Times Cited: 205
Multisite prediction of 4-week and 52-week treatment outcomes in patients with first-episode psychosis: a machine learning approach
Nikolaos Koutsouleris, René S. Kahn, Adam M. Chekroud, et al.
The Lancet Psychiatry (2016) Vol. 3, Iss. 10, pp. 935-946
Closed Access | Times Cited: 200
Review of Machine Learning Algorithms for Diagnosing Mental Illness
Gyeongcheol Cho, Jinyeong Yim, Younyoung Choi, et al.
Psychiatry Investigation (2019) Vol. 16, Iss. 4, pp. 262-269
Open Access | Times Cited: 196
Moving forward: how depression heterogeneity hinders progress in treatment and research
Eiko I. Fried
Expert Review of Neurotherapeutics (2017) Vol. 17, Iss. 5, pp. 423-425
Open Access | Times Cited: 186
Machine learning and big data in psychiatry: toward clinical applications
Robb B. Rutledge, Adam M. Chekroud, Quentin J. M. Huys
Current Opinion in Neurobiology (2019) Vol. 55, pp. 152-159
Open Access | Times Cited: 174
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
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