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Using machine learning to retrospectively predict self-reported gambling problems in Quebec.

W Spencer MurchSylvia KairouzSophie DauphinaisElyse PicardJean-Michel CostesMartin French
Published in: Addiction (Abingdon, England) (2023)
Machine learning algorithms appear to be able to classify at-risk online gamblers using data generated from their use of online gambling platforms. They may enable personalized harm prevention initiatives, but are constrained by trade-offs between their sensitivity and precision.
Keyphrases
  • machine learning
  • big data
  • health information
  • social media
  • artificial intelligence
  • mental health
  • deep learning
  • electronic health record
  • quality improvement
  • healthcare