AI Medical Compendium Topic

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Gambling

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Personality biomarkers of pathological gambling: A machine learning study.

Journal of neuroscience methods
BACKGROUND: The application of artificial intelligence to extract predictors of Gambling disorder (GD) is a new field of study. A plethora of studies have suggested that maladaptive personality dispositions may serve as risk factors for GD.

Applications of machine learning in addiction studies: A systematic review.

Psychiatry research
This study aims to provide a systematic review of the applications of machine learning methods in addiction research. In this study, multiple searches on MEDLINE, Embase and the Cochrane Database of Systematic Reviews were performed. 23 full-text art...

The Effectiveness of the Game of Dice Task in Predicting At-Risk and Problem Gambling Among Adolescents: The Contribution of the Neural Networks.

Journal of gambling studies
The Game of Dice Task (GDT; Brand et al. in Neuropsychology 19:267-277, 2005a; Psychiatry Res 133:91-99, 2005b) measures decision-making under objective risk conditions. Although disadvantageous decision-making has been shown in individuals with subs...

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...

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...

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...

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...

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 ...

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...

Online gambling forums as a potential target for harm reduction: an exploratory natural language processing analysis of a reddit.com forum.

Harm reduction journal
OBJECTIVES: Globally, there has been a rapid increase in the availability of online gambling. As online gambling has increased in popularity, there has been a corresponding increase in online communities that discuss gambling. The movement of gamblin...