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:
A preliminary risk prediction model for cannabis use disorder
Rajapaksha Mudalige Dhanushka S. Rajapaksha, Ryan Hammonds, Francesca M. Filbey, et al.
Preventive Medicine Reports (2020) Vol. 20, pp. 101228-101228
Open Access | Times Cited: 14
Rajapaksha Mudalige Dhanushka S. Rajapaksha, Ryan Hammonds, Francesca M. Filbey, et al.
Preventive Medicine Reports (2020) Vol. 20, pp. 101228-101228
Open Access | Times Cited: 14
Showing 14 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
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
Prevalence and correlates of cannabis use disorder among Australians using cannabis products to treat a medical condition
Llewellyn Mills, Nicholas Lintzeris, Michael O’Malley, et al.
Drug and Alcohol Review (2022) Vol. 41, Iss. 5, pp. 1095-1108
Open Access | Times Cited: 23
Llewellyn Mills, Nicholas Lintzeris, Michael O’Malley, et al.
Drug and Alcohol Review (2022) Vol. 41, Iss. 5, pp. 1095-1108
Open Access | Times Cited: 23
Applications of Machine Learning in Cannabis Research: A Scoping Review
Jeremy Y. Ng, Mrinal M. Lad, Dhruv Patel, et al.
European Journal of Integrative Medicine (2025)
Open Access
Jeremy Y. Ng, Mrinal M. Lad, Dhruv Patel, et al.
European Journal of Integrative Medicine (2025)
Open Access
Joint risk prediction for hazardous use of alcohol, cannabis, and tobacco among adolescents: A preliminary study using statistical and machine learning
Thanthirige Lakshika M Ruberu, Emily A. Kenyon, Karen A. Hudson, et al.
Preventive Medicine Reports (2021) Vol. 25, pp. 101674-101674
Open Access | Times Cited: 12
Thanthirige Lakshika M Ruberu, Emily A. Kenyon, Karen A. Hudson, et al.
Preventive Medicine Reports (2021) Vol. 25, pp. 101674-101674
Open Access | Times Cited: 12
Using Decision Trees to Identify Salient Predictors of Cannabis-Related Outcomes
Frank J. Schwebel, Dylan K. Richards, Rory A. Pfund, et al.
Journal of Psychoactive Drugs (2022) Vol. 54, Iss. 5, pp. 419-428
Open Access | Times Cited: 8
Frank J. Schwebel, Dylan K. Richards, Rory A. Pfund, et al.
Journal of Psychoactive Drugs (2022) Vol. 54, Iss. 5, pp. 419-428
Open Access | Times Cited: 8
A Bayesian learning model to predict the risk for cannabis use disorder
Rajapaksha Mudalige Dhanushka S. Rajapaksha, Francesca M. Filbey, Swati Biswas, et al.
Drug and Alcohol Dependence (2022) Vol. 236, pp. 109476-109476
Open Access | Times Cited: 8
Rajapaksha Mudalige Dhanushka S. Rajapaksha, Francesca M. Filbey, Swati Biswas, et al.
Drug and Alcohol Dependence (2022) Vol. 236, pp. 109476-109476
Open Access | Times Cited: 8
The screening of cannabis addiction using machine learning, MoCA, and anxiety/depression tests
Abdelilah Elhachimi, Abdelhafid Benksim, Hamid Ibanni, et al.
Scientific African (2024) Vol. 24, pp. e02225-e02225
Open Access | Times Cited: 1
Abdelilah Elhachimi, Abdelhafid Benksim, Hamid Ibanni, et al.
Scientific African (2024) Vol. 24, pp. e02225-e02225
Open Access | Times Cited: 1
Utility of Computational Approaches for Precision Psychiatry: Applications to Substance Use Disorders
Jasmin Vassileva, Jeung-Hyun Lee, Elena Psederska, et al.
Neuromethods (2023), pp. 211-231
Closed Access | Times Cited: 4
Jasmin Vassileva, Jeung-Hyun Lee, Elena Psederska, et al.
Neuromethods (2023), pp. 211-231
Closed Access | Times Cited: 4
How machine learning algorithms can examine patterns in multiple substance addictions: predicting the effects and interactions of psychoactive substances
Wafia Abada, Abdelkrim Bouramoul, Moustafa Sadek Kahil
International Journal of Computers and Applications (2024), pp. 1-11
Closed Access | Times Cited: 1
Wafia Abada, Abdelkrim Bouramoul, Moustafa Sadek Kahil
International Journal of Computers and Applications (2024), pp. 1-11
Closed Access | Times Cited: 1
Classical and Neural Network Machine Learning to Determine the Risk of Marijuana Use
Laura Zoboroski, Torrey Wagner, Brent Langhals
International Journal of Environmental Research and Public Health (2021) Vol. 18, Iss. 14, pp. 7466-7466
Open Access | Times Cited: 7
Laura Zoboroski, Torrey Wagner, Brent Langhals
International Journal of Environmental Research and Public Health (2021) Vol. 18, Iss. 14, pp. 7466-7466
Open Access | Times Cited: 7
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
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
Towards a New Dynamic Interaction Model of Adolescent CUD Manifestation, Prevention, and Treatment: A Narrative Review
Wesley Oosten, Elena Vos, Leontien Los, et al.
Psychoactives (2023) Vol. 2, Iss. 4, pp. 294-316
Open Access | Times Cited: 2
Wesley Oosten, Elena Vos, Leontien Los, et al.
Psychoactives (2023) Vol. 2, Iss. 4, pp. 294-316
Open Access | Times Cited: 2
Utility of computational approaches for precision psychiatry: Applications to substance use disorders
Jasmin Vassileva, Jeung Hyun Lee, Elena Psederska, et al.
(2022)
Open Access
Jasmin Vassileva, Jeung Hyun Lee, Elena Psederska, et al.
(2022)
Open Access
