Revolutionary AI technology enhances diagnosis of substance use disorder
Diagnostic tool could help speed treatment to patients
MSN, Bioengineer.org and other national news media outlets highlighted a novel artificial intelligence created by University of Cincinnati researchers that can help clinicians diagnose substance use disorder.
UC College of Engineering and Applied Science Professor Hans Breiter and Senior Research Associate Sumra Bari developed an AI system that can predict substance use defining behaviors with up to 83% accuracy and 84% accuracy to predict the severity of the addiction. Researchers say this could allow clinicians to provide treatment faster to patients who need it.
The study is one of the first of its kind to use a computational cognition framework with artificial intelligence to assess how human judgment can be used to predict substance use disorder defining behaviors, identify the substances used and determine the severity of the addiction.
“This is a new type of AI that can predict mental illness and commonly co-occurring conditions like addiction. It’s a low-cost first step for triage and assessment,” Breiter said.
The study was published in the Nature journal Mental Health Research.
Bioengineer.org described the UC system as both groundbreaking and revolutionary for the diagnosis and treatment of substance use disorder.
“Lower costs associated with this technology may lead to a significant reduction in barriers to care, ultimately resulting in improved health equity,“ Bioengineer reported.
Featured image at top: UC Professor Hans Breiter created a novel AI system that help predict substance use disorder. Photo/Andrew Higley/UC
More UC engineering in the news
UC developed a novel AI that can help diagnose substance use disorder with up to 83% accuracy. Photo/iStockPhoto
- Becker's Behavioral Health: UC tool predicts SUD with 83% accuracy
- Medical Dialogues: Powerful AI can help diagnose substance use disorder
- Medical XPress: AI can help diagnose substance use disorder, speed treatment
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