Researchers at the University of Denver, the Pennsylvania State University (Penn State), and the University of Southern California (USC) studied more than 1,600 youths in six states and used algorithms and machine learning to interpret the resulting data to determine how and when to intervene with regard to substance use disorder (SUC) in homeless youth.
Penn State's Amula Yadav developed the Comprehensive Opioid Response Tool Driven by Artificial Intelligence (CORTA), which considers multiple factors to predict one's likelihood of developing an opioid addiction.
USC's Aida Rahmattalabi developed the Group-based Intervention Decision aid (GUIDE) to assess an individual's social network to develop more effective intervention and recovery groups.
The researchers indicated that the use of artificial intelligence could help social workers identify youths at high risk of SUC and facilitate appropriate interventions.
From University of Denver
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Abstracts Copyright © 2020 SmithBucklin, Washington, DC, USA
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