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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 self-harm within six months after initial presentation to youth mental health services: A machine learning study
Frank Iorfino, Nicholas Ho, Joanne S. Carpenter, et al.
PLoS ONE (2020) Vol. 15, Iss. 12, pp. e0243467-e0243467
Open Access | Times Cited: 35

Showing 1-25 of 35 citing articles:

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
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: 35
Development of Personas and Journey Maps for Artificial Intelligence Agents Supporting the Use of Health Big Data: Human-Centered Design Approach
Yoon Heui Lee, Hanna Choi, Soo‐Kyoung Lee
JMIR Formative Research (2025) Vol. 9, pp. e67272-e67272
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
The Service Needs Index: A Tool to Quantify Complexity and Identify Treatment Needs in Youth Mental Health Services
William Capon, Ian B. Hickie, Mathew Varidel, et al.
Research Square (Research Square) (2025)
Closed Access
AI-based personalized real-time risk prediction for behavioral management in psychiatric wards using multimodal data
Ri-Ra Kang, Yong-gyom Kim, Minseok Hong, et al.
International Journal of Medical Informatics (2025), pp. 105870-105870
Closed Access
The temporal dependencies between social, emotional and physical health factors in young people receiving mental healthcare: a dynamic Bayesian network analysis
Frank Iorfino, Mathew Varidel, Roman Marchant, et al.
Epidemiology and Psychiatric Sciences (2023) Vol. 32
Open Access | Times Cited: 11
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
RETRACTED: PSCNN: PatchShuffle Convolutional Neural Network for COVID-19 Explainable Diagnosis
Shuihua Wang‎, Ziquan Zhu, Yudong Zhang
Frontiers in Public Health (2021) Vol. 9
Open Access | Times Cited: 22
Predictive modelling of deliberate self-harm and suicide attempts in young people accessing primary care: a machine learning analysis of a longitudinal study
Catherine McHugh, Nicholas Ho, Frank Iorfino, et al.
Social Psychiatry and Psychiatric Epidemiology (2023) Vol. 58, Iss. 6, pp. 893-905
Open Access | Times Cited: 8
Clinical staging and the differential risks for clinical and functional outcomes in young people presenting for youth mental health care
William Capon, Ian B. Hickie, Mathew Varidel, et al.
BMC Medicine (2022) Vol. 20, Iss. 1
Open Access | Times Cited: 12
Assessment of machine learning algorithms in national data to classify the risk of self-harm among young adults in hospital: A retrospective study
Anmol Arora, Louis Bojko, Santosh Kumar, et al.
International Journal of Medical Informatics (2023) Vol. 177, pp. 105164-105164
Open Access | Times Cited: 5
Mental Health Problems Prediction Using Machine Learning Techniques
Jia-Pao Cheng, Su-Cheng Haw
International Journal on Robotics Automation and Sciences (2023) Vol. 5, Iss. 2, pp. 59-72
Open Access | Times Cited: 4
Dynamic learning of individual-level suicidal ideation trajectories to enhance mental health care
Mathew Varidel, Ian B. Hickie, Ante Prodan, et al.
npj Mental Health Research (2024) Vol. 3, Iss. 1
Open Access | Times Cited: 1
Quantifying the interrelationships between physical, social, and cognitive-emotional components of mental fitness using digital technology
Frank Iorfino, Mathew Varidel, William Capon, et al.
npj Mental Health Research (2024) Vol. 3, Iss. 1
Open Access | Times Cited: 1
A Digital Approach for Addressing Suicidal Ideation and Behaviors in Youth Mental Health Services: Observational Study (Preprint)
Min K Chong, Ian B. Hickie, Antonia Ottavio, et al.
Journal of Medical Internet Research (2024)
Open Access | Times Cited: 1
Introduction to the PLOS ONE collection on ‘Understanding and preventing suicide: Towards novel and inclusive approaches’
Jo Robinson, Kairi Kõlves, Merike Sisask
PLoS ONE (2022) Vol. 17, Iss. 3, pp. e0264984-e0264984
Open Access | Times Cited: 5
Self-Harm in Aviation Medicine—A Complex Challenge During a Pandemic
Alpo Vuorio, Robert Bor
Frontiers in Public Health (2021) Vol. 9
Open Access | Times Cited: 6
Dynamic learning of individual-level suicidal ideation trajectories to enhance mental health care
Mathew Varidel, Ian B. Hickie, Ante Prodan, et al.
Research Square (Research Square) (2023)
Open Access | Times Cited: 2
Mental Health for Medical Students, what do we know today?
Vaidehi Yogeswaran, Christo El Morr
Procedia Computer Science (2022) Vol. 198, pp. 307-310
Open Access | Times Cited: 4
Editorial: Disrupting Pathways to Self-Harm in Adolescence: Machine Learning as an Opportunity
Lisa R. Fortuna
Journal of the American Academy of Child & Adolescent Psychiatry (2021) Vol. 60, Iss. 12, pp. 1459-1460
Closed Access | Times Cited: 4
Predictive Modeling, Artificial Intelligence, and Machine Learning in Psychiatric Assessment and Treatment
Donald M. Hilty, Abraham Peled, David D. Luxton
Springer eBooks (2024), pp. 5217-5238
Closed Access
Processing Grief and Emotional Loss Through Mindfulness in Virtual Reality
Davide Maria Marchioro, Aimée Argüero Fonseca, Fabio Benatti, et al.
(2024), pp. 143-167
Closed Access
Using machine learning to assist decision making in the assessment of mental health patients presenting to emergency departments
Oliver Higgins, Rhonda Wilson, Stephan K. Chalup
Digital Health (2024) Vol. 10
Open Access
A Digital Approach for Addressing Suicidal Ideation and Behaviors in Youth Mental Health Services: Observational Study (Preprint)
Min K Chong, Ian B. Hickie, Antonia Ottavio, et al.
(2024)
Closed Access
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