Development and evaluation of a risk algorithm predicting alcohol dependence after early onset of regular alcohol use.

Chrianna BharatMeyer D GlantzSergio Aguilar-GaxiolaJordi AlonsoRonny BruffaertsBrendan BuntingJosé Miguel Caldas-de-AlmeidaGraça CardosoStephanie ChardoulPeter de JongeOye GurejeJosep Maria HaroMeredith G HarrisElie G KaramNorito KawakamiAndrzej KiejnaViviane Kovess-MasfetySing LeeJohn G McGrathJacek MoskalewiczFernando Navarro-MateuCharlene RapseyNancy A SampsonKate M ScottHisateru TachimoriMargreet Ten HaveGemma VilagutBogdan WojtyniakMiguel XavierRonald C KesslerLouisa Degenhardt

Published in: Addiction (Abingdon, England) (2023)

A risk algorithm can be created using data collected at the onset of regular alcohol use to target youth at highest risk of alcohol dependence by early adulthood. Important considerations remain for advancing the development and practical implementation of such models.

Keyphrases

early onset
machine learning
late onset
deep learning
primary care
healthcare
physical activity
young adults
alcohol consumption
depressive symptoms
electronic health record
quality improvement
neural network