Toward Fairness in Machine Learning Models for Predicting Treatment Retention and Premature Discontinuation in Medication for Opioid Use Disorder

Addressing algorithmic bias to ensure equitable patient retention in opioid use disorder treatment programs.

Persistent low retention and completion rates in medications for opioid use disorder (MOUD) have driven the use of machine learning (ML) models to predict retention and identify patients at risk of premature discontinuation. However, the fairness of these models across patient po...

ArXiv CS.LG2026-09-22