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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 Suicides After Psychiatric Hospitalization in US Army Soldiers
Ronald C. Kessler, Christopher H. Warner, Christopher Ivany, et al.
JAMA Psychiatry (2014) Vol. 72, Iss. 1, pp. 49-49
Open Access | Times Cited: 429

Showing 26-50 of 429 citing articles:

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: 162
Artificial Intelligence and Suicide Prevention: A Systematic Review of Machine Learning Investigations
Rebecca A. Bernert, Amanda M. 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: 160
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: 150
Machine learning model to predict mental health crises from electronic health records
Roger Garriga, Javier Mas, Semhar Abraha, et al.
Nature Medicine (2022) Vol. 28, Iss. 6, pp. 1240-1248
Open Access | Times Cited: 100
Artificial intelligence for Sustainable Development Goals: Bibliometric patterns and concept evolution trajectories
Aakash Singh, Anurag Kanaujia, Vivek Kumar Singh, et al.
Sustainable Development (2023) Vol. 32, Iss. 1, pp. 724-754
Open Access | Times Cited: 59
Machine learning and the prediction of suicide in psychiatric populations: a systematic review
Alessandro Pigoni, Giuseppe Delvecchio, Nunzio Turtulici, et al.
Translational Psychiatry (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 20
Dissociation debates: everything you know is wrong
Richard J. Loewenstein
Dialogues in Clinical Neuroscience (2018) Vol. 20, Iss. 3, pp. 229-242
Open Access | Times Cited: 158
Novel Use of Natural Language Processing (NLP) to Predict Suicidal Ideation and Psychiatric Symptoms in a Text-Based Mental Health Intervention in Madrid
Benjamin Lê Cook, Ana M. Progovac, Pei Chen, et al.
Computational and Mathematical Methods in Medicine (2016) Vol. 2016, pp. 1-8
Open Access | Times Cited: 155
Predicting suicides after outpatient mental health visits in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS)
Ronald C. Kessler, Murray B. Stein, Maria Petukhova, et al.
Molecular Psychiatry (2016) Vol. 22, Iss. 4, pp. 544-551
Open Access | Times Cited: 150
Meta-analysis of suicide rates in the first week and the first month after psychiatric hospitalisation
D. Chung, Dušan Pavlović, Maggie Haitian Wang, et al.
BMJ Open (2019) Vol. 9, Iss. 3, pp. e023883-e023883
Open Access | Times Cited: 145
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
Association of Child Abuse Exposure With Suicidal Ideation, Suicide Plans, and Suicide Attempts in Military Personnel and the General Population in Canada
Tracie O. Afifi, Tamara Taillieu, Mark A. Zamorski, et al.
JAMA Psychiatry (2016) Vol. 73, Iss. 3, pp. 229-229
Open Access | Times Cited: 135
Machine learning in suicide science: Applications and ethics
Kathryn P. Linthicum, Katherine Musacchio Schafer, Jessica D. Ribeiro
Behavioral Sciences & the Law (2019) Vol. 37, Iss. 3, pp. 214-222
Closed Access | Times Cited: 130
Predicting mental health problems in adolescence using machine learning techniques
Ashley Tate, Ryan C. McCabe, Henrik Larsson, et al.
PLoS ONE (2020) Vol. 15, Iss. 4, pp. e0230389-e0230389
Open Access | Times Cited: 129
Big data analytics and machine learning: 2015 and beyond
Ives Cavalcante Passos, Benson Mwangi, Flávio Kapczinski
The Lancet Psychiatry (2016) Vol. 3, Iss. 1, pp. 13-15
Closed Access | Times Cited: 121
Improving Prediction of Suicide and Accidental Death After Discharge From General Hospitals With Natural Language Processing
Thomas H. McCoy, Víctor M. Castro, Ashlee M Roberson, et al.
JAMA Psychiatry (2016) Vol. 73, Iss. 10, pp. 1064-1064
Open Access | Times Cited: 121
Prediction of Sex-Specific Suicide Risk Using Machine Learning and Single-Payer Health Care Registry Data From Denmark
Jaimie L. Gradus, Anthony J. Rosellini, Erzsébet Horváth‐Puhó, et al.
JAMA Psychiatry (2019) Vol. 77, Iss. 1, pp. 25-25
Open Access | Times Cited: 121
Effect of Augmenting Standard Care for Military Personnel With Brief Caring Text Messages for Suicide Prevention
Katherine Anne Comtois, Amanda H. Kerbrat, Christopher R. DeCou, et al.
JAMA Psychiatry (2019) Vol. 76, Iss. 5, pp. 474-474
Open Access | Times Cited: 120
Significant shared heritability underlies suicide attempt and clinically predicted probability of attempting suicide
Douglas M. Ruderfer, Colin G. Walsh, Matthew Aguirre, et al.
Molecular Psychiatry (2019) Vol. 25, Iss. 10, pp. 2422-2430
Open Access | Times Cited: 120
Suicidal Risk Following Hospital Discharge: A Review
Alberto Forte, Andrea Buscajoni, Andrea Fiorillo, et al.
Harvard Review of Psychiatry (2019) Vol. 27, Iss. 4, pp. 209-216
Closed Access | Times Cited: 120
Advancing the Understanding of Suicide: The Need for Formal Theory and Rigorous Descriptive Research
Alexander J. Millner, Donald J. Robinaugh, Matthew K. Nock
Trends in Cognitive Sciences (2020) Vol. 24, Iss. 9, pp. 704-716
Open Access | Times Cited: 117
The use of electronic health records for psychiatric phenotyping and genomics
Jordan W. Smoller
American Journal of Medical Genetics Part B Neuropsychiatric Genetics (2017) Vol. 177, Iss. 7, pp. 601-612
Open Access | Times Cited: 116
Association Between Social Integration and Suicide Among Women in the United States
Alexander C. Tsai, Michel Lucas, Ichiro Kawachi
JAMA Psychiatry (2015) Vol. 72, Iss. 10, pp. 987-987
Open Access | Times Cited: 115
Understanding suicide risk within the Research Domain Criteria (RDoC) framework: A meta-analytic review
Catherine R. Glenn, Evan M. Kleiman, B. Christine, et al.
Depression and Anxiety (2017) Vol. 35, Iss. 1, pp. 65-88
Open Access | Times Cited: 115
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: 106

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