Improving Opioid Use Disorder Risk Modelling through Behavioral and Genetic Feature Integration

arXiv:2309.10837v2 Announce Type: replace-cross
Abstract: Opioids are an effective analgesic for acute and chronic pain, but also carry a considerable risk of addiction leading to millions of opioid use disorder (OUD) cases and tens of thousands of premature deaths in the United States yearly. Estimating OUD risk prior to prescription could improve the efficacy of treatment regimens, monitoring programs, and intervention strategies, but risk estimation is typically based on self-reported data or questionnaires. We develop an experimental design and computational …

abstract addiction arxiv cases cs.cy cs.lg feature improving integration modelling opioid pain prior q-bio.qm risk through type united united states