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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:

Predeployment predictors of psychiatric disorder‐symptoms and interpersonal violence during combat deployment
Anthony J. Rosellini, Murray B. Stein, David M. Benedek, et al.
Depression and Anxiety (2018) Vol. 35, Iss. 11, pp. 1073-1080
Open Access | Times Cited: 21

Showing 21 citing articles:

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: 159
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: 54
Pre-deployment risk factors for PTSD in active-duty personnel deployed to Afghanistan: a machine-learning approach for analyzing multivariate predictors
Katharina Schultebraucks, Meng Qian, Duna Abu‐Amara, et al.
Molecular Psychiatry (2020) Vol. 26, Iss. 9, pp. 5011-5022
Open Access | Times Cited: 90
The use of machine learning techniques in trauma-related disorders: a systematic review
Luís Francisco Ramos-Lima, Vitória Waikamp, Thyago Antonelli-Salgado, et al.
Journal of Psychiatric Research (2019) Vol. 121, pp. 159-172
Closed Access | Times Cited: 82
The psychiatric dysfunctions associated to the labor estrés in professionals of the education
María de las Nieves Veloz Montano
Interdisciplinary Rehabilitation / Rehabilitacion Interdisciplinaria (2023) Vol. 3, pp. 60-60
Open Access | Times Cited: 23
Development and Validation of a Machine Learning Prediction Model of Posttraumatic Stress Disorder After Military Deployment
Santiago Papini, Sonya B. Norman, Laura Campbell‐Sills, et al.
JAMA Network Open (2023) Vol. 6, Iss. 6, pp. e2321273-e2321273
Open Access | Times Cited: 17
Genome‐wide analyses of psychological resilience in U.S. Army soldiers
Murray B. Stein, Karmel W. Choi, Sonia Jain, et al.
American Journal of Medical Genetics Part B Neuropsychiatric Genetics (2019) Vol. 180, Iss. 5, pp. 310-319
Open Access | Times Cited: 45
Military Applications of Machine Learning: A Bibliometric Perspective
José Javier Galán-Hernández, R.A. Carrasco, Antonio LaTorre
Mathematics (2022) Vol. 10, Iss. 9, pp. 1397-1397
Open Access | Times Cited: 23
The use of machine learning on administrative and survey data to predict suicidal thoughts and behaviors: a systematic review
Nibene Habib Somé, Pardis Noormohammadpour, Shannon Lange
Frontiers in Psychiatry (2024) Vol. 15
Open Access | Times Cited: 3
Common and specific determinants of 9-year depression and anxiety course-trajectories: A machine-learning investigation in the Netherlands Study of Depression and Anxiety (NESDA).
Klaas J. Wardenaar, Harriëtte Riese, Erik J. Giltay, et al.
Journal of Affective Disorders (2021) Vol. 293, pp. 295-304
Open Access | Times Cited: 16
Pre-deployment predictors of suicide attempt during and after combat deployment: Results from the Army Study to Assess Risk and Resilience in Servicemembers
Kelly L. Zuromski, Samantha L. Bernecker, Carol Chu, et al.
Journal of Psychiatric Research (2019) Vol. 121, pp. 214-221
Open Access | Times Cited: 16
<p>Machine Learning Methods to Evaluate the Depression Status of Chinese Recruits: A Diagnostic Study</p>
Mengxue Zhao, Zhengzhi Feng
Neuropsychiatric Disease and Treatment (2020) Vol. Volume 16, pp. 2743-2752
Open Access | Times Cited: 11
Effects of prior deployments and perceived resilience on anger trajectories of combat-deployed soldiers
Laura Campbell‐Sills, Jason Kautz, Karmel W. Choi, et al.
Psychological Medicine (2021) Vol. 53, Iss. 5, pp. 2031-2040
Open Access | Times Cited: 10
Applicability of an Automated Model and Parameter Selection in the Prediction of Screening-Level PTSD in Danish Soldiers Following Deployment: Development Study of Transferable Predictive Models Using Automated Machine Learning
Karen‐Inge Karstoft, Ioannis Tsamardinos, Kasper Eskelund, et al.
JMIR Medical Informatics (2020) Vol. 8, Iss. 7, pp. e17119-e17119
Open Access | Times Cited: 8
Employing body-fixed sensors and machine learning to predict physical activity in military personnel
Nikolaos Papadakis, Konstantinos Havenetidis, Dimitris Papadopoulos, et al.
BMJ Military Health (2020) Vol. 169, Iss. 2, pp. 152-156
Open Access | Times Cited: 7
Early prediction of mental health problems following military deployment: Integrating pre- and post-deployment factors in neural network models
Karen‐Inge Karstoft, Kasper Eskelund, Jaimie L. Gradus, et al.
Journal of Psychiatric Research (2023) Vol. 163, pp. 109-117
Closed Access | Times Cited: 2
Predicting Suicidal Behavior Among Indian Adults Using Childhood Trauma, Mental Health Questionnaires and Machine Learning Cascade Ensembles
Akash K Rao, Gunjan Y Trivedi, Riri G. Trivedi, et al.
Lecture notes in networks and systems (2024), pp. 247-257
Closed Access
Operaciones militares, despliegues de tropa y alteraciones en salud mental: una revisión de la literatura
Cesar Andrés Fernández-Duarte, Manuel David Flores-Pedroso, Sebastián Gonzales-Calle, et al.
Brújula Semilleros de Investigación (2024) Vol. 12, Iss. 23, pp. 48-73
Open Access
Genomewide Analyses of Psychological Resilience in US Army Soldiers
Murray B. Stein, Karmel W. Choi, Sonia Jain, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2019)
Open Access
Applicability of an Automated Model and Parameter Selection in the Prediction of Screening-Level PTSD in Danish Soldiers Following Deployment: Development Study of Transferable Predictive Models Using Automated Machine Learning (Preprint)
Karen‐Inge Karstoft, Ioannis Tsamardinos, Kasper Eskelund, et al.
(2019)
Open Access
Visual Analysis of Domestic and Foreign Resilience Research in the Past Fifteen Years Based on CiteSpace
美阳 王
Traditional Chinese Medicine (2022) Vol. 11, Iss. 02, pp. 196-207
Closed Access
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