[HTML][HTML] A survey on detecting mental disorders with natural language processing: Literature review, trends and challenges
A Montejo-Ráez, MD Molina-González… - Computer Science …, 2024 - Elsevier
For years, the scientific community has researched monitoring approaches for the detection
of certain mental disorders and risky behaviors, like depression, eating disorders, gambling …
of certain mental disorders and risky behaviors, like depression, eating disorders, gambling …
The Ravaging Effects of Online Gambling on The Social Functioning of Male Breadwinners In African Families
CM Rammutla - Innovation Journal of Social Sciences and Economic …, 2024 - ijsser.com
This systematic review examines the ravaging effects of online gambling on the social
functioning of male breadwinners in African families. Online gambling negatively impacts the …
functioning of male breadwinners in African families. Online gambling negatively impacts the …
[HTML][HTML] Establishing the temporal stability of machine learning models that detect online gambling-related harms
WS Murch, S Kairouz, M French - Computers in Human Behavior Reports, 2024 - Elsevier
Artificial Intelligence (AI) models can detect at-risk online gamblers by analyzing patterns in
their betting behaviour, but their performance over time has not been assessed. Linking …
their betting behaviour, but their performance over time has not been assessed. Linking …
Comparing 'fair'machine learning models for detecting at-risk online gamblers
WS Murch, S Kairouz, M French - International Gambling Studies, 2024 - Taylor & Francis
Researchers have worked to develop machine learning models that detect at-risk online
gamblers, enabling personalized harm prevention tools. However, existing research has not …
gamblers, enabling personalized harm prevention tools. However, existing research has not …
30-Month revalidation to determine the temporal stability of machine learning models for detecting online gambling-related harms
WS Murch, S Kairouz, M French - 2023 - osf.io
Abstract Background and Aims: Machine learning algorithms can detect at-risk online
gamblers by analyzing patterns in betting behaviour. Example models have been tested in …
gamblers by analyzing patterns in betting behaviour. Example models have been tested in …