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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 alcohol use disorder remission: a longitudinal multimodal multi-featured machine learning approach
Sivan Kinreich, Vivia V. McCutcheon, Fazil Alıev, et al.
Translational Psychiatry (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 36

Showing 1-25 of 36 citing articles:

How machine learning is used to study addiction in digital healthcare: A systematic review
Bijoy Chhetri, Lalit Mohan Goyal, Mamta Mittal
International Journal of Information Management Data Insights (2023) Vol. 3, Iss. 2, pp. 100175-100175
Open Access | Times Cited: 23
Multimodal Fusion of Brain Imaging Data: Methods and Applications
Na Luo, Weiyang Shi, Zhengyi Yang, et al.
Deleted Journal (2024) Vol. 21, Iss. 1, pp. 136-152
Open Access | Times Cited: 11
Evaluation of Risk of Bias in Neuroimaging-Based Artificial Intelligence Models for Psychiatric Diagnosis
Zhiyi Chen, Xuerong Liu, Qingwu Yang, et al.
JAMA Network Open (2023) Vol. 6, Iss. 3, pp. e231671-e231671
Open Access | Times Cited: 19
Sampling inequalities affect generalization of neuroimaging-based diagnostic classifiers in psychiatry
Zhiyi Chen, Bowen Hu, Xuerong Liu, et al.
BMC Medicine (2023) Vol. 21, Iss. 1
Open Access | Times Cited: 17
Multimodal-based machine learning approach to classify features of internet gaming disorder and alcohol use disorder: A sensor-level and source-level resting-state electroencephalography activity and neuropsychological study
Jiyoon Lee, Myeong Seop Song, So Young Yoo, et al.
Comprehensive Psychiatry (2024) Vol. 130, pp. 152460-152460
Open Access | Times Cited: 7
The Collaborative Study on the Genetics of Alcoholism: Overview
Arpana Agrawal, Sarah J. Brislin, Kathleen K. Bucholz, et al.
Genes Brain & Behavior (2023) Vol. 22, Iss. 5
Open Access | Times Cited: 16
The collaborative study on the genetics of alcoholism: Sample and clinical data
Danielle M. Dick, Emily Balcke, Vivia V. McCutcheon, et al.
Genes Brain & Behavior (2023) Vol. 22, Iss. 5
Open Access | Times Cited: 13
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
Machine learning models and AI in predicting diagnosis and prognosis in alcohol-related and metabolic dysfunction-associated steatotic liver disease
Akash Roy, Nipun Verma
Metabolism and Target Organ Damage (2025) Vol. 5, Iss. 1
Open Access
The collaborative study on the genetics of alcoholism: Brain function
Jacquelyn L. Meyers, Sarah J. Brislin, Chella Kamarajan, et al.
Genes Brain & Behavior (2023) Vol. 22, Iss. 5
Open Access | Times Cited: 10
Drinking behavior patterns may be associated with persistent depressive symptoms after alcohol abstinence in alcohol use disorder
Kazuhiro Kurihara, Hotaka Shinzato, Yoshikazu Takaesu, et al.
Neuropsychopharmacology Reports (2024) Vol. 44, Iss. 2, pp. 381-388
Open Access | Times Cited: 3
Multimodal frontal neuroimaging markers predict longitudinal craving reduction in abstinent individuals with heroin use disorder
Xinwen Wen, Wenhan Yang, Zhe Du, et al.
Journal of Psychiatric Research (2024) Vol. 177, pp. 1-10
Closed Access | Times Cited: 3
Implications of neuroimaging findings in addiction
Xinwen Wen, Lirong Yue, Zhe Du, et al.
Deleted Journal (2023) Vol. 3
Open Access | Times Cited: 7
Classifying Different Types of Smokers and Drinkers by Analyzing Body Signals using Machine Learning
Rakib Hasan, Ferdous Hasan, Md Mehedi Hasan, et al.
2022 9th International Conference on Computing for Sustainable Global Development (INDIACom) (2024), pp. 1060-1064
Closed Access | Times Cited: 2
A scoping review of electroencephalographic (EEG) markers for tracking neurophysiological changes and predicting outcomes in substance use disorder treatment
Tarik Bel‐Bahar, Anam A. Khan, Riaz Shaik, et al.
Frontiers in Human Neuroscience (2022) Vol. 16
Open Access | Times Cited: 10
The Influence of Using Novel Predictive Technologies on Judgments of Stigma, Empathy, and Compassion among Healthcare Professionals
Daniel Z. Buchman, Daphne Imahori, Christopher Lo, et al.
AJOB Neuroscience (2023) Vol. 15, Iss. 1, pp. 32-45
Open Access | Times Cited: 6
Using machine learning to predict heavy drinking during outpatient alcohol treatment
Walter Roberts, Yize Zhao, Terril L. Verplaetse, et al.
Alcoholism Clinical and Experimental Research (2022) Vol. 46, Iss. 4, pp. 657-666
Open Access | Times Cited: 9
The potential of electroencephalography coherence to predict the outcome of repetitive transcranial magnetic stimulation in insomnia disorder
Xiaozi Zhang, Xumeng Zhao, Ziqiang Shao, et al.
Journal of Psychiatric Research (2023) Vol. 160, pp. 56-63
Closed Access | Times Cited: 5
Drinking and smoking polygenic risk is associated with childhood and early-adulthood psychiatric and behavioral traits independently of substance use and psychiatric genetic risk
Flavio De Angelis, Frank R. Wendt, Gita A. Pathak, et al.
Translational Psychiatry (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 11
Disentangling heterogeneity in substance use disorder: Insights from genome-wide polygenic scores
Laura Vilar‐Ribó, Judit Cabana‐Domínguez, Silvia Alemany, et al.
Translational Psychiatry (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
The Implications of Leveraging Administrative Data for Public Health Approaches to Protecting Children: Sleepwalking into Quicksand?
Bob Lonne, Todd I. Herrenkohl, Daryl Higgins, et al.
International Journal on Child Maltreatment Research Policy and Practice (2022) Vol. 5, Iss. 4, pp. 501-517
Closed Access | Times Cited: 6
Predicting Alcohol-Related Memory Problems in Older Adults: A Machine Learning Study with Multi-Domain Features
Chella Kamarajan, Ashwini K. Pandey, David B. Chorlian, et al.
Behavioral Sciences (2023) Vol. 13, Iss. 5, pp. 427-427
Open Access | Times Cited: 2
The use of class imbalanced learning methods on ULSAM data to predict the case–control status in genome-wide association studies
Ragıp Onur ÖZTORNACI, Hamzah Syed, Andrew P. Morris, et al.
Journal Of Big Data (2023) Vol. 10, Iss. 1
Open 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
Occupational factors associated with long-term abstinence among persons treated for alcohol dependence
Sinu Ezhumalai, D. Muralidhar, Pratima Murthy
Indian Journal of Occupational and Environmental Medicine (2022) Vol. 26, Iss. 2, pp. 122-128
Closed Access | Times Cited: 3
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