Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Prospective prediction of suicide attempts in community adolescents and young adults, using regression methods and machine learning
Marcel Miché, Erich Studerus, Andrea H. Meyer, et al.
Journal of Affective Disorders (2019) Vol. 265, pp. 570-578
Closed Access | Times Cited: 48

Showing 1-25 of 48 citing articles:

Daily runoff forecasting by deep recursive neural network
Jiang-Wei Zhang, Xiaohui Chen, Amirul Khan, et al.
Journal of Hydrology (2021) Vol. 596, pp. 126067-126067
Closed Access | Times Cited: 97
Artificial intelligence and suicide prevention: A systematic review
Alban Lejeune, Aziliz Le Glaz, Pierre-Antoine Perron, et al.
European Psychiatry (2022) Vol. 65, Iss. 1
Open Access | Times Cited: 55
Annual Research Review: Translational machine learning for child and adolescent psychiatry
Dominic Dwyer, Nikolaos Koutsouleris
Journal of Child Psychology and Psychiatry (2022) Vol. 63, Iss. 4, pp. 421-443
Open Access | Times Cited: 40
Prediction of non-suicidal self-injury in adolescents at the family level using regression methods and machine learning
Si Chen Zhou, Zhaohe Zhou, Qi Tang, et al.
Journal of Affective Disorders (2024) Vol. 352, pp. 67-75
Closed Access | Times Cited: 12
Protective factors for suicidal ideation and suicide attempts in adolescence: a longitudinal population-based cohort study examining sex differences
Victoria Bakken, Stian Lydersen, Norbert Skokauskas, et al.
BMC Psychiatry (2025) Vol. 25, Iss. 1
Open Access | Times Cited: 1
Suicidal behaviour prediction models using machine learning techniques: A systematic review
Noratikah Nordin, Zurinahni Zainol, Mohd Halim Mohd Noor, et al.
Artificial Intelligence in Medicine (2022) Vol. 132, pp. 102395-102395
Closed Access | Times Cited: 36
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: 6
Analysis and evaluation of explainable artificial intelligence on suicide risk assessment
Hao Tang, Aref Miri Rekavandi, Dharjinder Rooprai, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 6
Predicting short-term suicidal thoughts in adolescents using machine learning: developing decision tools to identify daily level risk after hospitalization
Ewa K. Czyz, Hyun Jung Koo, Nadia Al‐Dajani, et al.
Psychological Medicine (2021) Vol. 53, Iss. 7, pp. 2982-2991
Open Access | Times Cited: 36
Predicting suicide attempts among Norwegian adolescents without using suicide-related items: a machine learning approach
E. F. Haghish, Nikolai Olavi Czajkowski, Tilmann von Soest
Frontiers in Psychiatry (2023) Vol. 14
Open Access | Times Cited: 13
A survey on detecting mental disorders with natural language processing: Literature review, trends and challenges
Arturo Montejo‐Ráez, M. Dolores Molina-González, Salud María Jiménez-Zafra, et al.
Computer Science Review (2024) Vol. 53, pp. 100654-100654
Open Access | Times Cited: 4
Behavioral and social predictors of suicidal ideation and attempts among adolescents and young adults
Yeganeh Shahsavar, Avishek Choudhury
PLOS mental health. (2025) Vol. 2, Iss. 1, pp. e0000221-e0000221
Open Access
Psychiatric Disorders and Adverse Life Events as Suicidality Predictors in Disadvantaged Youth from a Leading Institution of Mental Health: A Machine Learning Approach
María Elena Márquez-Caraveo, Blanca Estela Barcelata Eguiarte, Hortensia Moreno-Macías, et al.
Research Square (Research Square) (2025)
Open Access
Predicting treatment response to cognitive behavior therapy in social anxiety disorder on the basis of demographics, psychiatric history, and scales: A machine learning approach
Qasim Bukhari, David Rosenfield, Stefan G. Hofmann, et al.
PLoS ONE (2025) Vol. 20, Iss. 3, pp. e0313351-e0313351
Open Access
Unveiling sex difference in factors associated with suicide attempt among Chinese adolescents with depression: a machine learning-based study
Yang Wang, Siyu Chen, J Y Liu, et al.
Journal of Mental Health (2025), pp. 1-11
Closed Access
Explainable artificial intelligence models for predicting risk of suicide using health administrative data in Quebec
Fatemeh Gholi Zadeh Kharrat, Christian Gagné, Alain Lesage, et al.
PLoS ONE (2024) Vol. 19, Iss. 4, pp. e0301117-e0301117
Open Access | Times Cited: 3
Psychological pain and sociodemographic factors classified suicide attempt and non-suicidal self-injury in adolescents
Jiamin Bao, Jiachen Wan, Huanhuan Li, et al.
Acta Psychologica (2024) Vol. 246, pp. 104271-104271
Open Access | Times Cited: 3
Utility of item 9 of the patient health questionnaire in the prospective identification of adolescents at risk of suicide attempt
Robert B. Penfold, Ursula Whiteside, Eric Johnson, et al.
Suicide and Life-Threatening Behavior (2021) Vol. 51, Iss. 5, pp. 854-863
Closed Access | Times Cited: 23
Comparison of traditional model-based statistical methods with machine learning for the prediction of suicide behaviour
Leandro Nicolás Grendas, Luciana Carla Chiapella, Demián Rodante, et al.
Journal of Psychiatric Research (2021) Vol. 145, pp. 85-91
Closed Access | Times Cited: 23
Saving Lives: Recognizing and Intervening with Youth at Risk for Suicide
Alejandra Arango, Polly Y. Gipson, Jennifer G. Votta, et al.
Annual Review of Clinical Psychology (2021) Vol. 17, Iss. 1, pp. 259-284
Open Access | Times Cited: 21
5-year incidence of suicide-risk in youth: A gradient tree boosting and SHAP study
Pedro L. Ballester, Taiane de Azevedo Cardoso, Fernanda Pedrotti Moreira, et al.
Journal of Affective Disorders (2021) Vol. 295, pp. 1049-1056
Closed Access | Times Cited: 18
Predicting adolescent depression and anxiety from multi-wave longitudinal data using machine learning
Mariah T. Hawes, H. Andrew Schwartz, Youngseo Son, et al.
Psychological Medicine (2022) Vol. 53, Iss. 13, pp. 6205-6211
Closed Access | Times Cited: 13
A Comprehensive Review of Computer-Aided Diagnosis of Major Mental and Neurological Disorders and Suicide: A Biostatistical Perspective on Data Mining
Mahsa Mansourian, Sadaf Khademi, Hamid Reza Marateb
Diagnostics (2021) Vol. 11, Iss. 3, pp. 393-393
Open Access | Times Cited: 16
Predicting suicide attempts and suicide deaths among adolescents following outpatient visits
Robert B. Penfold, Eric Johnson, Susan M. Shortreed, et al.
Journal of Affective Disorders (2021) Vol. 294, pp. 39-47
Open Access | Times Cited: 16
Highlighting psychological pain avoidance and decision‐making bias as key predictors of suicide attempt in major depressive disorder—A novel investigative approach using machine learning
Xinlei Ji, Jiahui Zhao, Lejia Fan, et al.
Journal of Clinical Psychology (2021) Vol. 78, Iss. 4, pp. 671-691
Closed Access | Times Cited: 16
Page 1 - Next Page

Scroll to top