AIMC Topic: Gambling

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Identifying EEG-based neurobehavioral risk markers of gaming addiction using machine learning and iowa gambling task.

Biomedical physics & engineering express
Internet Gaming Disorder (IGD), Gaming Disorder (GD), and Internet Addiction represent behavioral patterns with significant psychological and neurological consequences. Affected individuals often disengage from routine activities and exhibit distress...

Cross-jurisdictional factors linked to gambling frequency in adolescents from 28 European countries: a machine learning approach.

Psychiatry research
Adolescents are vulnerable to experiencing problematic gambling, although its prevalence and potential risk factors vary across countries. This study aims to identify cross-jurisdictional factors associated with higher gambling frequency among adoles...

Assessing the risk of problem gambling among lottery loyalty program members: A machine learning approach.

Addictive behaviors
BACKGROUND AND AIMS: Lottery gambling is a relatively benign form of gambling. Nonetheless, individuals with gambling problems may engage in lottery play and/or play the lottery exclusively. Lottery loyalty programs have data that could be used to sc...

Stigmatisation of gambling disorder in social media: a tailored deep learning approach for YouTube comments.

Harm reduction journal
BACKGROUND: The stigmatisation of gamblers, particularly those with a gambling disorder, and self-stigmatisation are considered substantial barriers to seeking help and treatment. To develop effective strategies to reduce the stigma associated with g...

Insights into the temporal dynamics of identifying problem gambling on an online casino: A machine learning study on routinely collected individual account data.

Journal of behavioral addictions
BACKGROUND AND AIMS: The digitalization of gambling provides unprecedented opportunities for early identification of problem gambling, a well-recognized public health issue. This study aimed to advance current practices by employing advanced machine ...

The lived experience of gambling-related harm in natural language.

Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors
OBJECTIVE: Gambling-related harms can have a significant negative impact on disordered gamblers, lower risk gamblers, and affected others. Yet, most disordered and lower risk gamblers will never seek formal treatment, often due to the stigma and sham...

Illegal Online Gambling Site Detection using Multiple Resource-Oriented Machine Learning.

Journal of gambling studies
The COVID-19 pandemic has led to faster digitalization and illegal online gambling has become popular. As illegal online gambling brings not only financial threats but also breaches in overall cyber security, this study defines the concept of absolut...

Unmasking Risky Habits: Identifying and Predicting Problem Gamblers Through Machine Learning Techniques.

Journal of gambling studies
The use of machine learning techniques to identify problem gamblers has been widely established. However, existing methods often rely on self-reported labeling, such as temporary self-exclusion or account closure. In this study, we propose a novel ap...

Machine learning-based analysis of adolescent gambling factors.

Journal of behavioral addictions
BACKGROUND AND AIMS: Problem gambling among adolescents has recently attracted attention because of easy access to gambling in online environments and its serious effects on adolescent lives. We proposed a machine learning-based analysis method for p...

Decoding and mapping task states of the human brain via deep learning.

Human brain mapping
Support vector machine (SVM)-based multivariate pattern analysis (MVPA) has delivered promising performance in decoding specific task states based on functional magnetic resonance imaging (fMRI) of the human brain. Conventionally, the SVM-MVPA requir...