AI helps clarify complex array and interaction of risk factors contributing to alcohol use disorder

Explainable AI (xAI) models are illuminating the multiple risk factors that underlie the development of alcohol use disorder (AUD), according to a new study. Although some factors involved in AUD—including demographic, socioeconomic and genetic variables—are known, researchers typically study them in isolation, and their roles in individuals' risk are often small. The variability of AUD presentations, meanwhile, reflects unique personal combinations of genetic, environmental, neurobiological and psychosocial factors. Understanding their relative influence and how these variables interact could better predict the risk of dangerous drinking and inform tailored prevention and treatment approaches.

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