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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:

Machine learning with neuroimaging biomarkers: Application in the diagnosis and prediction of drug addiction
Longtao Yang, Yanyao Du, Wenhan Yang, et al.
Addiction Biology (2023) Vol. 28, Iss. 2
Closed Access | Times Cited: 20

Showing 20 citing articles:

Connectome-based predictive modeling of Internet addiction symptomatology
Qiuyang Feng, Zhiting Ren, Dongtao Wei, et al.
Social Cognitive and Affective Neuroscience (2024) Vol. 19, Iss. 1
Open Access | Times Cited: 13
The ReCoDe addiction research consortium: Losing and regaining control over drug intake—Findings and future perspectives
Rainer Spanagel, Patrick Bach, Tobias Banaschewski, et al.
Addiction Biology (2024) Vol. 29, Iss. 7
Open Access | Times Cited: 10
IUPHAR Review: New strategies for medications to treat substance use disorders
Iván D. Montoya, Nora D. Volkow
Pharmacological Research (2024) Vol. 200, pp. 107078-107078
Open Access | Times Cited: 7
Updated Perspectives on the Neurobiology of Substance Use Disorders Using Neuroimaging
Kevin S. Murnane, Amber N. Edinoff, Elyse M. Cornett, et al.
Substance Abuse and Rehabilitation (2023) Vol. Volume 14, pp. 99-111
Open Access | Times Cited: 13
Discriminative functional connectivity signature of cocaine use disorder links to rTMS treatment response
Kanhao Zhao, Gregory A. Fonzo, Hua Xie, et al.
Nature Mental Health (2024) Vol. 2, Iss. 4, pp. 388-400
Open Access | Times Cited: 5
Unveiling causal relationships between tobacco use phenotypes and neuroimaging: Insights from bidirectional Mendelian randomization and bibliometric analysis
Zhiyong Zhang, Longtao Yang, H.R. Guan, et al.
Brain Research Bulletin (2025) Vol. 223, pp. 111277-111277
Open Access
The Neuroscience of Addiction
Toheeb O. Oyerinde, Abraham Olufemi Asuku, Tobiloba Samuel Olajide, et al.
Advances in medical education, research, and ethics (AMERE) book series (2025), pp. 289-322
Closed Access
Unmasking the Brain in Cocaine Use Disorder: A Deep Learning Approach with Graph Convolutional Networks and Principal Component Analysis
M. Matinfar, Mozafar Bag-Mohammdi, Mojtaba Karami
Next research. (2025), pp. 100304-100304
Closed Access
Artificial Intelligence-driven and technological innovations in the diagnosis and management of substance use disorders
Daniela Lé Tassinari, Maria Olívia Pozzolo Pedro, Manoela Pozzolo Pedro, et al.
International Review of Psychiatry (2024), pp. 1-7
Closed Access | Times Cited: 2
The gut microbiota as a potential biomarker for methamphetamine use disorder: evidence from two independent datasets
Linzi Liu, Zijing Deng, Wen Liu, et al.
Frontiers in Cellular and Infection Microbiology (2023) Vol. 13
Open Access | Times Cited: 5
Assessment of rTMS treatment effects for methamphetamine addiction based on EEG functional connectivity
Yongcong Li, Banghua Yang, Jun Ma, et al.
Cognitive Neurodynamics (2024) Vol. 18, Iss. 5, pp. 2373-2386
Closed Access | Times Cited: 1
Analyzing Dropout in Alcohol Recovery Programs: A Machine Learning Approach
Adele Collin, Adrián Ayuso-Muñoz, Paloma Tejera Nevado, et al.
Journal of Clinical Medicine (2024) Vol. 13, Iss. 16, pp. 4825-4825
Open Access | Times Cited: 1
A generalizable functional connectivity signature characterizes brain dysfunction and links to rTMS treatment response in cocaine use disorder
Kanhao Zhao, Gregory A. Fonzo, Hua Xie, et al.
medRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 4
Application of omics-based biomarkers in substance use disorders
Longtao Yang, Lijie Zhang, Huiting Zhang, et al.
Meta-Radiology (2023) Vol. 1, Iss. 1, pp. 100008-100008
Open Access | Times Cited: 3
Drug Use and Artificial Intelligence: Weighing Concerns and Possibilities for Prevention
Jerel M. Ezell, Babatunde Patrick Ajayi, Tapan Parikh, et al.
American Journal of Preventive Medicine (2023) Vol. 66, Iss. 3, pp. 568-572
Closed Access | Times Cited: 3
Predicting the Cerebral Blood Flow Change Condition during Brain Strokes using Feature Fusion of FMRI Images and Clinical Features
Vandana Sharma, Anurag Sinha, Michael Wiryaseputra, et al.
2022 13th International Conference on Computing Communication and Networking Technologies (ICCCNT) (2023)
Closed Access | Times Cited: 2
Exploring the potential of the metaverse medical paradigm in drug addiction treatment: a preliminary discussion and future prospects
Longtao Yang, Lijie Zhang, Wenhan Yang, et al.
General Psychiatry (2023) Vol. 36, Iss. 6, pp. e101258-e101258
Open Access | Times Cited: 2
Temporal-Spatial Conversion Based Sequential Convolutional LSTM Architecture for Detecting Drug Addiction
Haiping Ma, Jiuyi Yao, Jiyuan Huang, et al.
IEEE Signal Processing Letters (2024) Vol. 31, pp. 1785-1789
Closed Access
Craving for a Robust Methodology: A Systematic Review of Machine Learning Algorithms on Substance-Use Disorders Treatment Outcomes
Bernardo Paim de Mattos, Christian Mattjie, Rafaela Ravazio, et al.
International Journal of Mental Health and Addiction (2024)
Open Access
FBSA-CNN: A convolutional neural network framework for EEG-based detection of non-acute methamphetamine use disorders
Yongcong Li, Banghua Yang, Yonghuai Zhang, et al.
Biomedical Signal Processing and Control (2024) Vol. 100, pp. 106985-106985
Closed Access
A Method to Detect Amphetamine Addiction using Shallow Learning and Deep Learning
Harsh Saran, Saurav Kumar, Aleena Swetapadma, et al.
(2024), pp. 1-6
Closed Access
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