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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 classify suicide attempt history among youth in medical care settings
Taylor A. Burke, Ross Jacobucci, Brooke A. Ammerman, et al.
Journal of Affective Disorders (2020) Vol. 268, pp. 206-214
Closed Access | Times Cited: 34

Showing 1-25 of 34 citing articles:

An explainable predictive model for suicide attempt risk using an ensemble learning and Shapley Additive Explanations (SHAP) approach
Noratikah Nordin, Zurinahni Zainol, Mohd Halim Mohd Noor, et al.
Asian Journal of Psychiatry (2022) Vol. 79, pp. 103316-103316
Closed Access | Times Cited: 72
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
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
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
Clinician Suicide Risk Assessment for Prediction of Suicide Attempt in a Large Health Care System
Kate H. Bentley, Chris J. Kennedy, Pratik N. Khadse, et al.
JAMA Psychiatry (2025)
Closed Access
Decoding vital variables in predicting different phases of suicide among young adults with childhood sexual abuse: a machine learning approach
Wenbang Niu, Yi Feng, Jiaqi Li, et al.
Translational Psychiatry (2025) Vol. 15, Iss. 1
Open Access
Artificial Intelligence, Machine Learning Approach and Suicide Prevention: A Qualitative Narrative Review
Sheikh Shoib, Mohd Faizan Siddiqui, Serkan Turan, et al.
Deleted Journal (2025)
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
Prediction of Mental Health Problem Using Annual Student Health Survey: Machine Learning Approach
Ayako Baba, Kyosuke Bunji
JMIR Mental Health (2022) Vol. 10, pp. e42420-e42420
Open Access | Times Cited: 15
Are false positives in suicide classification models a risk group? Evidence for “true alarms” in a population-representative longitudinal study of Norwegian adolescents
E. F. Haghish, Bruno Laeng, Nikolai Olavi Czajkowski
Frontiers in Psychology (2023) Vol. 14
Open Access | Times Cited: 8
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
Predicting inmate suicidal behavior with an interpretable ensemble machine learning approach in smart prisons
Khayyam Akhtar, Muhammad Usman Yaseen, Muhammad Imran, et al.
PeerJ Computer Science (2024) Vol. 10, pp. e2051-e2051
Open Access | Times Cited: 2
Reconsidering False Positives in Machine Learning Binary Classification Models of Suicidal Behavior
E. F. Haghish, Nikolai Olavi Czajkowski
Current Psychology (2023) Vol. 43, Iss. 11, pp. 10117-10121
Open Access | Times Cited: 6
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
Suicide Screening Tools for Pediatric Emergency Department Patients: A Systematic Review
Amanda Scudder, R. David Rosin, Becky Baltich Nelson, et al.
Frontiers in Psychiatry (2022) Vol. 13
Open Access | Times Cited: 8
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
Understanding current states of machine learning approaches in medical informatics: a systematic literature review
Najmul Hasan, Yukun Bao
Health and Technology (2021) Vol. 11, Iss. 3, pp. 471-482
Closed Access | Times Cited: 10
Mental health impact of COVID-19 and machine learning applications in combating mental disorders: a review
Chirantan Ganguly, Sagnik Nayak, Anil K. Gupta
Elsevier eBooks (2022), pp. 1-51
Closed Access | Times Cited: 7
Prediction of recurrent suicidal behavior among suicide attempters with Cox regression and machine learning: a 10-year prospective cohort study
Yan-Xin Wei, Bao-Peng Liu, Jie Zhang, et al.
Journal of Psychiatric Research (2021) Vol. 144, pp. 217-224
Closed Access | Times Cited: 6
Analyzing and Predicting Learner Sentiment Toward Specialty Schools Using Machine Learning Techniques
Md Shamim Hossain, Mst Farjana Rahman, Md. Kutub Uddin
Advances in educational technologies and instructional design book series (2022), pp. 133-158
Closed Access | Times Cited: 4
Prediction of Mental Health Problem Using Annual Student Health Survey: Machine Learning Approach (Preprint)
Ayako Baba, Kyosuke Bunji
(2022)
Open Access | Times Cited: 3
Decoding Vital Variables in Predicting Different Phases of Suicide Among Young Adults with Childhood Sexual Abuse: A Machine Learning Approach
W D Niu, Yi Feng, Jiaqi Li, et al.
(2024)
Closed Access
Development and Validation of a Machine Learning Model for Detection and Classification of Vertigo
Xiaowu Tang, W. Ye, Yongkang Ou, et al.
The Laryngoscope (2024)
Closed Access
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