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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:

Using Machine Learning to Predict Suicide Attempts in Military Personnel
David C. Rozek, William C. Andres, Noelle B. Smith, et al.
Psychiatry Research (2020) Vol. 294, pp. 113515-113515
Open Access | Times Cited: 27

Showing 1-25 of 27 citing articles:

Artificial intelligence in mental health care: a systematic review of diagnosis, monitoring, and intervention applications
Pablo Cruz-Gonzalez, Anxun He, Eva K. M. Lam, et al.
Psychological Medicine (2025) Vol. 55
Closed Access | Times Cited: 3
Development of an efficient cement production monitoring system based on the improved random forest algorithm
Hanane Zermane, Abbes Drardja
The International Journal of Advanced Manufacturing Technology (2022) Vol. 120, Iss. 3-4, pp. 1853-1866
Open Access | Times Cited: 31
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
Artificial intelligence: its potential in personalized public health strategies and genetic data analysis: a narrative review
Gülcan Demir Özdenk, Zeynep Yeğin
Personalized Medicine (2025), pp. 1-9
Closed Access
Predicting Lifetime Suicide Attempts in a Community Sample of Adolescents Using Machine Learning Algorithms
Kristin Jankowsky, Diana Steger, Ulrich Schroeders
Assessment (2023) Vol. 31, Iss. 3, pp. 557-573
Open Access | Times Cited: 9
Artificial Intelligence-Based Suicide Prevention and Prediction: A Systematic Review (2019-2023)
Anirudh Atmakuru, Alen Shahini, Subrata Chakraborty, et al.
(2024)
Closed Access | Times Cited: 3
The impact of machine learning in predicting risk of violence: A systematic review
Giovanna Parmigiani, Benedetta Barchielli, Simona Casale, et al.
Frontiers in Psychiatry (2022) Vol. 13
Open Access | Times Cited: 15
Predicting suicidality with small sets of interpretable reward behavior and survey variables
Shamal Lalvani, Sumra Bari, Nicole L. Vike, et al.
Nature Mental Health (2024) Vol. 2, Iss. 7, pp. 773-786
Open Access | Times Cited: 2
A New Classification Model Using a Decision Tree Generated from Hyperplanes in Dimensional Space
B. Luna-Benoso, J. C. Martínez-Perales, Úrsula Samantha Morales-Rodríguez, et al.
Applied Artificial Intelligence (2024) Vol. 38, Iss. 1
Open Access | Times Cited: 2
Structured data vs. unstructured data in machine learning prediction models for suicidal behaviors: A systematic review and meta-analysis
Danielle Hopkins, Debra Rickwood, David John Hallford, et al.
Frontiers in Digital Health (2022) Vol. 4
Open Access | Times Cited: 9
Sleep continuity, timing, quality, and disorder are associated with suicidal ideation and suicide attempts among college students
Andrew Tubbs, Krishna Taneja, Sadia Ghani, et al.
Journal of American College Health (2023) Vol. 72, Iss. 9, pp. 3357-3365
Closed Access | Times Cited: 5
Leveraging data science to enhance suicide prevention research: a literature review
Avital Rachelle Wulz, Royal Law, Jing Wang, et al.
Injury Prevention (2021) Vol. 28, Iss. 1, pp. 74-80
Open Access | Times Cited: 11
Automatically extracting social determinants of health for suicide: a narrative literature review
Annika Marie Schoene, Suzanne Garverich, Iman Ibrahim, et al.
npj Mental Health Research (2024) Vol. 3, Iss. 1
Open Access | Times Cited: 1
Classification of Adolescent Psychiatric Patients at High Risk of Suicide Using the Personality Assessment Inventory by Machine Learning
Kyung-Won Kim, Jae Seok Lim, Chan-Mo Yang, et al.
Psychiatry Investigation (2021) Vol. 18, Iss. 11, pp. 1137-1143
Open Access | Times Cited: 10
Courses of suicidal ideation among military veterans in residential treatment for posttraumatic stress disorder
Noelle B. Smith, Lauren M. Sippel, David C. Rozek, et al.
Depression and Anxiety (2020) Vol. 37, Iss. 3, pp. 273-284
Open Access | Times Cited: 6
Machine Learning Methods for Stress Monitoring using Wearable Devices
Samvad Gour, C. N. S. Vinoth Kumar
2022 International Conference on Electronics and Renewable Systems (ICEARS) (2022), pp. 1346-1352
Closed Access | Times Cited: 3
Intelligent Control System of a Real Industrial Process
Hanane ZERMANE, Hassina Madjour
The Eurasia Proceedings of Science Technology Engineering and Mathematics (2022) Vol. 19, pp. 61-67
Open Access | Times Cited: 3
Artificial Intelligence and Large Language Models in Mental Healthcare

(2024), pp. 195-215
Closed Access
Artificial Intelligence-based Suicide Prevention and Prediction: A Systematic Review (2019-2023)
Anirudh Atmakuru, Alen Shahini, Subrata Chakraborty, et al.
Information Fusion (2024), pp. 102673-102673
Closed Access
Transforming Industrial Supervision Systems: A Comprehensive Approach Integrating Machine Learning Techniques and Fuzzy Logic
Hanane Zermane, Ahcene Ziar, Hassina Madjour, et al.
˜The œScientific Bulletin of Electrical Engineering Faculty (2024) Vol. 24, Iss. 2, pp. 52-66
Open Access
Predicting Lifetime Suicide Attempts in a Community Sample of Adolescents Using Machine Learning Algorithms
Kristin Jankowsky, Diana Steger, Ulrich Schroeders
(2022)
Open Access | Times Cited: 1
Machine Learning
Chandril Chandan Ghosh
Springer eBooks (2022), pp. 87-156
Closed Access | Times Cited: 1
Development of an Efficient Cement Production Monitoring System Based on the Improved Random Forest Algorithm
Hanane Zermane, Abbes Drardja
Research Square (Research Square) (2021)
Open Access | Times Cited: 1
Deep Learning and Natural Language Processing-Based Model for the Prediction of Suicidal Ideation in Military Personnel
Sapna Katoch, Balwinder Kaur Dhaliwal, Gurpreet Singh
(2023), pp. 508-514
Closed Access
Fine-Grained Assessment of Nonsuicidal Self-Injury
Nicole K. Legg, Andrew C. Switzer, Brianna J. Turner
Oxford University Press eBooks (2023), pp. 912-929
Closed Access
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