{"id":185593,"date":"2026-02-05T22:48:00","date_gmt":"2026-02-06T03:48:00","guid":{"rendered":"https:\/\/testing.news-you-need.com\/index.php\/2026\/02\/05\/artificial-intelligence-enables-faster-detection-of-substance-use-disorder\/"},"modified":"2026-02-08T14:01:01","modified_gmt":"2026-02-08T19:01:01","slug":"artificial-intelligence-enables-faster-detection-of-substance-use-disorder","status":"publish","type":"post","link":"https:\/\/testing.news-you-need.com\/index.php\/2026\/02\/05\/artificial-intelligence-enables-faster-detection-of-substance-use-disorder\/","title":{"rendered":"Artificial intelligence enables faster detection of substance use disorder"},"content":{"rendered":"<p><a href=\"https:\/\/www.news-medical.net\/news\/20260205\/Artificial-intelligence-enables-faster-detection-of-substance-use-disorder.aspx\">Artificial intelligence enables faster detection of substance use disorder<\/a><\/p>\n<p><a href=\"https:\/\/www.news-medical.net\/news\/20260205\/Artificial-intelligence-enables-faster-detection-of-substance-use-disorder.aspx\">https:\/\/www.news-medical.net\/news\/20260205\/Artificial-intelligence-enables-faster-detection-of-substance-use-disorder.aspx<\/a><\/p>\n<p>Publish Date: <a href=\"publish_date]\">2026-02-05 22:48:00<\/a><\/p>\n<p>Source Domain: <a href=\"www.news-medical.net\">www.news-medical.net<\/a><\/p>\n<ul>\n<li>A new artificial intelligence system developed by the University of Cincinnati can predict substance use disorder-defining behaviors with up to 83% accuracy and the severity of addiction with up to 84% accuracy.<\/li>\n<li>The AI system uses a computational cognition framework, alongside traditional questionnaires and judgments about mildly emotional stimuli in the form of 48 pictures.<\/li>\n<li>The study represents an innovative use of AI to assess and predict mental illnesses, potentially expanding to behavioral addictions such as social media, gaming, or excessive food consumption.<\/li>\n<li>The researchers emphasize the system&#8217;s cost-effectiveness, scalability, and resilience to manipulation, potentially offering a low-cost, accessible first step for triage and assessment in mental health.<\/li>\n<li>The identification accuracy of the substances used (e.g., stimulants, opioids, cannabis) reached up to 82%. <\/li>\n<li>The AI system evaluated various behavioral economic concepts to formulate a profile of individuals with substance use disorder characterized by increased risk-seeking and reduced resilience to losses.<\/li>\n<li>The study examined 3,476 participants, providing data for the machine learning algorithms to predict behaviors accurately.<\/li>\n<li>The study was published in the Nature journal Mental Health Research and is proposed to enable assessment across a broader spectrum of addictions.<\/li>\n<\/ul>\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Artificial intelligence enables faster detection of substance use disorder https:\/\/www.news-medical.net\/news\/20260205\/Artificial-intelligence-enables-faster-detection-of-substance-use-disorder.aspx Publish Date: 2026-02-05 22:48:00 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