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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:

Applications of machine learning in addiction studies: A systematic review
Kwok Kei Mak, Kounseok Lee, Cheolyong Park
Psychiatry Research (2019) Vol. 275, pp. 53-60
Closed Access | Times Cited: 110

Showing 1-25 of 110 citing articles:

Machine Learning Approaches for Combating Distributed Denial of Service Attacks in Modern Networking Environments
Ahamed Aljuhani
IEEE Access (2021) Vol. 9, pp. 42236-42264
Open Access | Times Cited: 113
Computational intelligence-based classification system for the diagnosis of memory impairment in psychoactive substance users
Chaoyang Zhu
Journal of Cloud Computing Advances Systems and Applications (2024) Vol. 13, Iss. 1
Open Access | Times Cited: 22
Improving Mental Health Services: A 50-Year Journey from Randomized Experiments to Artificial Intelligence and Precision Mental Health
Leonard Bickman
Administration and Policy in Mental Health and Mental Health Services Research (2020) Vol. 47, Iss. 5, pp. 795-843
Open Access | Times Cited: 137
Coupling RBF neural network with ensemble learning techniques for landslide susceptibility mapping
Binh Thai Pham, T. Nguyen‐Thoi, Chongchong Qi, et al.
CATENA (2020) Vol. 195, pp. 104805-104805
Closed Access | Times Cited: 134
Precision Psychiatry Applications with Pharmacogenomics: Artificial Intelligence and Machine Learning Approaches
Eugene Lin, Chieh‐Hsin Lin, Hsien‐Yuan Lane
International Journal of Molecular Sciences (2020) Vol. 21, Iss. 3, pp. 969-969
Open Access | Times Cited: 117
Multi-site clustering and nested feature extraction for identifying autism spectrum disorder with resting-state fMRI
Nan Wang, Dongren Yao, Lizhuang Ma, et al.
Medical Image Analysis (2021) Vol. 75, pp. 102279-102279
Closed Access | Times Cited: 60
Psychiatry in the Digital Age: A Blessing or a Curse?
Carl B. Roth, Andreas Papassotiropoulos, Annette Beatrix Brühl, et al.
International Journal of Environmental Research and Public Health (2021) Vol. 18, Iss. 16, pp. 8302-8302
Open Access | Times Cited: 46
Artificial intelligence and its impact on the domains of universal health coverage, health emergencies and health promotion: An overview of systematic reviews
Antonio Martínez-Millana, Aida Saez-Saez, Roberto Tornero-Costa, et al.
International Journal of Medical Informatics (2022) Vol. 166, pp. 104855-104855
Open Access | Times Cited: 36
A Systematic Review and Bibliometric Analysis of Applications of Artificial Intelligence and Machine Learning in Vascular Surgery
Arshia Javidan, Allen Li, Michael H. Lee, et al.
Annals of Vascular Surgery (2022) Vol. 85, pp. 395-405
Closed Access | Times Cited: 35
Machine learning for predicting opioid use disorder from healthcare data: A systematic review
Christian Garbin, Nicholas Marques, Oge Marques
Computer Methods and Programs in Biomedicine (2023) Vol. 236, pp. 107573-107573
Closed Access | Times Cited: 18
Machine learning applications in tobacco research: a scoping review
Rui Fu, Anasua Kundu, Nicholas Mitsakakis, et al.
Tobacco Control (2021) Vol. 32, Iss. 1, pp. 99-109
Closed Access | Times Cited: 40
The Ethics of AI in Games
Dávid Melhárt, Julian Togelius, Benedikte Mikkelsen, et al.
IEEE Transactions on Affective Computing (2023) Vol. 15, Iss. 1, pp. 79-92
Closed Access | Times Cited: 13
Duty of care, data science, and gambling harm: A scoping review of risk assessment models
Virve Marionneau, Kim Ristolainen, Tomi Roukka
Computers in Human Behavior Reports (2025), pp. 100644-100644
Open Access
A novel deep neural network approach to detect and monitor cocaine drug abuse
Aleena Swetapadma, Divya Kumari
Computers in Biology and Medicine (2025) Vol. 191, pp. 110130-110130
Closed Access
Predictors of treatment attrition among individuals in substance use disorder treatment: A machine learning approach
Jill A. Rabinowitz, Jonathan Wells, Geoffrey Kahn, et al.
Addictive Behaviors (2025), pp. 108265-108265
Closed Access
A methodological exploration of feature selection techniques to enhance AI-based predictive analytics in public health
Ali Ünlü, Pekka Hakkarainen, Karoliina Karjalainen, et al.
Elsevier eBooks (2025), pp. 325-359
Closed Access
Improving diagnosis-based quality measures: an application of machine learning to the prediction of substance use disorder among outpatients
Katherine J. Hoggatt, Alex H. S. Harris, Corey J. Hayes, et al.
BMJ Open Quality (2025) Vol. 14, Iss. 1, pp. e003017-e003017
Open Access
Predictors of smartphone addiction in adolescents with depression: combing the machine learning and moderated mediation model approach
Yongjie Zhou, Chenran Pei, Hai-Long Yin, et al.
Behaviour Research and Therapy (2025), pp. 104749-104749
Closed Access
Correlates of past year suicidal thoughts among sexual and gender minority young adults: A machine learning analysis
Anasua Kundu, Rui Fu, Daniel Grace, et al.
Journal of Psychiatric Research (2022) Vol. 152, pp. 269-277
Closed Access | Times Cited: 18
An efficient Apriori algorithm for frequent pattern in human intoxication data
Md. Mehedi Hassan, Sadika Zaman, Swarnali Mollick, et al.
Innovations in Systems and Software Engineering (2023) Vol. 19, Iss. 1, pp. 61-69
Closed Access | Times Cited: 9
Predictors of perceived success in quitting smoking by vaping: A machine learning approach
Rui Fu, Robert Schwartz, Nicholas Mitsakakis, et al.
PLoS ONE (2022) Vol. 17, Iss. 1, pp. e0262407-e0262407
Open Access | Times Cited: 15
Practical foundations of machine learning for addiction research. Part I. Methods and techniques
Pablo Cresta Morgado, Martín Carusso, Laura Alonso Alemany, et al.
The American Journal of Drug and Alcohol Abuse (2022) Vol. 48, Iss. 3, pp. 260-271
Open Access | Times Cited: 14
Applications of data science for responsible gambling: a scoping review
Kasra Ghaharian, Brett Abarbanel, Dylan Phung, et al.
International Gambling Studies (2022) Vol. 23, Iss. 2, pp. 289-312
Closed Access | Times Cited: 14
Predicting alcohol dependence treatment outcomes: a prospective comparative study of clinical psychologists versus ‘trained’ machine learning models
Martyn Symons, Gerald F.X. Feeney, Marcus Gallagher, et al.
Addiction (2020) Vol. 115, Iss. 11, pp. 2164-2175
Closed Access | Times Cited: 23
Machine Learning for Predicting the Surface Plasmon Resonance of Perfect and Concave Gold Nanocubes
Jesús Andrés Arzola-Flores, A. L. González
The Journal of Physical Chemistry C (2020) Vol. 124, Iss. 46, pp. 25447-25454
Closed Access | Times Cited: 22
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