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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 predict opioid misuse among U.S. adolescents
Dae‐Hee Han, Shieun Lee, Dong‐Chul Seo
Preventive Medicine (2019) Vol. 130, pp. 105886-105886
Closed Access | Times Cited: 52

Showing 1-25 of 52 citing articles:

Evaluation of artificial intelligence techniques in disease diagnosis and prediction
Nafiseh Ghaffar Nia, Erkan Kaplanoğlu, Ahad Nasab
Discover Artificial Intelligence (2023) Vol. 3, Iss. 1
Open Access | Times Cited: 169
Machine-learning approaches to substance-abuse research: emerging trends and their implications
Elan Barenholtz, Nicole D. Fitzgerald, William Edward Hahn
Current Opinion in Psychiatry (2020) Vol. 33, Iss. 4, pp. 334-342
Closed Access | Times Cited: 57
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
Artificial intelligence and public health
K. Lee, B. Gandhi, Jonathan A. Tangsrivimol, et al.
Elsevier eBooks (2025), pp. 127-157
Closed Access
Opioid death projections with AI-based forecasts using social media language
Matthew Matero, Salvatore Giorgi, Brenda Curtis, et al.
npj Digital Medicine (2023) Vol. 6, Iss. 1
Open Access | Times Cited: 11
Utilizing Machine Learning for Early Intervention and Risk Management in the Opioid Overdose Crisis
Andy Man Yeung Tai, Alireza Kazemi, Jane J. Kim, et al.
Wiley Interdisciplinary Reviews Computational Statistics (2025) Vol. 17, Iss. 1
Open 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
Identifying Predictors of Opioid Overdose Death at a Neighborhood Level With Machine Learning
Robert C. Schell, Bennett Allen, William C. Goedel, et al.
American Journal of Epidemiology (2021) Vol. 191, Iss. 3, pp. 526-533
Open Access | Times Cited: 26
Individualized Prospective Prediction of Opioid Use Disorder
Yang S. Liu, Lawrence Kiyang, Jake Hayward, et al.
The Canadian Journal of Psychiatry (2022) Vol. 68, Iss. 1, pp. 54-63
Open Access | Times Cited: 16
Prediction of sustained opioid use in children and adolescents using machine learning
Dor Atias, Aviv Tuttnauer, Noam Shomron, et al.
British Journal of Anaesthesia (2024) Vol. 133, Iss. 2, pp. 351-359
Closed Access | Times Cited: 3
Predictive analysis using machine learning: Review of trends and methods
Patrick Loola Bokonda, Khadija Ouazzani-Touhami, Nissrine Souissi
(2020), pp. 1-6
Closed Access | Times Cited: 24
Machine learning model for diagnostic method prediction in parasitic disease using clinical information
You Won Lee, Jae Woo Choi, Eun‐Hee Shin
Expert Systems with Applications (2021) Vol. 185, pp. 115658-115658
Open Access | Times Cited: 19
Identifying emerging predictors for adolescent electronic nicotine delivery systems use: A machine learning analysis of the Population Assessment of Tobacco and Health Study
Dae‐Hee Han, Shin Hyung Lee, Shieun Lee, et al.
Preventive Medicine (2021) Vol. 145, pp. 106418-106418
Closed Access | Times Cited: 18
From machine learning to deep learning: A comprehensive study of alcohol and drug use disorder
Banafsheh Rekabdar, David L. Albright, Justin T. McDaniel, et al.
Healthcare Analytics (2022) Vol. 2, pp. 100104-100104
Open Access | Times Cited: 13
Nonmedical Opioid Use After Short-term Therapeutic Exposure in Children: A Systematic Review
Malema Ahrari, Samina Ali, Lisa Hartling, et al.
PEDIATRICS (2021) Vol. 148, Iss. 6
Open Access | Times Cited: 11
Machine Learned Classification of Ligand Intrinsic Activities at Humanµ-Opioid Receptor
Myongin Oh, Maximilian Shen, Ruibin Liu, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 1
Machine Learned Classification of Ligand Intrinsic Activities at Human μ-Opioid Receptor
Myongin Oh, Maximilian Shen, Ruibin Liu, et al.
ACS Chemical Neuroscience (2024) Vol. 15, Iss. 15, pp. 2842-2852
Open Access | Times Cited: 1
Artificial intelligence and opioid use: a narrative review
Seema Gadhia, Georgia C. Richards, Tracey Marriott, et al.
BMJ Innovations (2022) Vol. 9, Iss. 2, pp. 78-96
Open Access | Times Cited: 5
Feature Extraction for Heroin-Use Classification Using Imbalanced Random Forest Methods
Matthew Beattie, Charles Nicholson
Substance Use & Misuse (2020) Vol. 56, Iss. 1, pp. 123-130
Closed Access | Times Cited: 6
Risk prediction model for cannabis use with artificial intelligence approach
Ali Ünlü, Pekka Hakkarainen, Karoliina Karjalainen, et al.
Journal of Substance Use (2023) Vol. 29, Iss. 6, pp. 1077-1084
Closed Access | Times Cited: 2
Beyond cocaine and heroin use: a stacking ensemble-based framework for predicting the likelihood of subsequent substance use disorder using demographics and personality traits
Amina Bouhadja, Abdelkrim Bouramoul
International Journal of Computers and Applications (2023) Vol. 45, Iss. 11, pp. 722-733
Closed Access | Times Cited: 2
Optimizing Substance Use Treatment Selection Using Reinforcement Learning
Matt Baucum, Anahita Khojandi, Carole R. Myers, et al.
ACM Transactions on Management Information Systems (2022) Vol. 14, Iss. 2, pp. 1-30
Closed Access | Times Cited: 4
A Psychosocial Approach to Predicting Substance Use Disorder (SUD) Among Adolescents
Adway S. Wadekar
2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (2020)
Closed Access | Times Cited: 5
Use of Machine Learning Methods in Psychiatry
İlkim Ecem Emre, Cumhur Taş, Çiğdem Erol
Psikiyatride Guncel Yaklasimlar - Current Approaches in Psychiatry (2021) Vol. 13, Iss. 2, pp. 332-353
Open Access | Times Cited: 5
Data Driven Classification of Opioid Patients Using Machine Learning–An Investigation
Saddam Al Amin, Md. Saddam Hossain Mukta, Md. Sezan Mahmud Saikat, et al.
IEEE Access (2022) Vol. 11, pp. 396-409
Open Access | Times Cited: 3
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