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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 Suicidal Behavior Without Asking About Suicidal Ideation: Machine Learning and the Role of Borderline Personality Disorder Criteria
Adam Horvath, Mark Dras, Catie C. W. Lai, et al.
Suicide and Life-Threatening Behavior (2020) Vol. 51, Iss. 3, pp. 455-466
Closed Access | Times Cited: 13

Showing 13 citing articles:

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
A Longitudinal Prediction of Suicide Attempts in Borderline Personality Disorder: A Machine Learning Study
L. Fortaner-Uyà, Camilla Monopoli, Marco Cavicchioli, et al.
Journal of Clinical Psychology (2025)
Closed Access
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
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
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: 2
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
AI ethics in computational psychiatry: From the neuroscience of consciousness to the ethics of consciousness
Wanja Wiese, Karl Friston
Behavioural Brain Research (2021) Vol. 420, pp. 113704-113704
Open Access | Times Cited: 15
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: 8
Detection of antisocial personality disorder using optimal multi-head attention based auto encoder
A. Rohini, A. Packialatha
Multimedia Tools and Applications (2024)
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
Predicting self-harm at one year in female prisoners: a retrospective cohort study using machine learning
Paul A. Tiffin, Sant Leelamanthep, Lewis W. Paton, et al.
medRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access
Contribución de las Tecnologías de la Información y las Comunicaciones para ayudar a la prevención del Comportamiento Suicida en Castilla y León: Un enfoque de Machine Learning y Salud Digital.
Gema Castillo-Sánchez
(2023)
Open Access
P.227 Prediction of suicidal behaviour by evaluating personality traids with machine learning techniques
Yesne Alici, Hüseyin Öztoprak, Jamal Hasanlı, et al.
European Neuropsychopharmacology (2021) Vol. 44, pp. S34-S35
Closed Access
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