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White populations have higher rates of Substance Use Disorder (SUD) than Black, Asian, and Hispanic populations. This includes addictions to tobacco, alcohol, marijuana, and prescription drugs. However, cultural and ethnic minorities are at higher risk for facing economic and cultural barriers in the diagnosis and treatment of substance use disorders. For example, 88.7% of Black Americans with substance abuse disorders do not seek or receive addiction treatment. Substance abuse is also critically tied to mental health — in 2014, 20.2 million adults in the U.S. had a substance use disorder and 7.9 million had both a substance use disorder and another mental illness. Furthermore, alcohol use disorder for Native Americans is 7.1%, which is disproportionately high compared to the 5.4% proportion of the general population.
Tobacco is the most common subtype of SUD. Smoking is a leading cause of preventable death and of the 34M smokers in the US, 20M want to quit.
Identifying and reducing triggers: Deep learning can predict environmental triggers to smoking, such as a park bench. This approach may lead to development of therapies that trigger “just-in-time adaptive cessation interventions” and help a smoker optimize their environment for smoking reduction.
Rapid, novel drug treatment for addiction can help curb the effects of dependency and withdrawal.