A Machine Learning Application to Classify Patients at Differing Levels of Risk of Opioid Use Disorder: Clinician-Based Validation Study.
Tewodros EgualeFrançois BastardotWenyu SongDaniel Motta-CalderonYasmin ElsobkyAngela RuiMarlika MarceauClark DavisSandya GanesanAva AlsubaiMichele L MatthewsLynn A VolkDavid Westfall BatesRonen RozenblumPublished in: JMIR medical informatics (2024)
A systematic comparison was conducted between an ML application and clinicians for identifying OUD risk. The ML application generated clinically valid and useful alerts about patients' different OUD risk levels. ML applications hold promise for identifying patients at differing levels of OUD risk and will likely complement traditional rule-based approaches to generating alerts about opioid safety issues.