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Candidate Genes from an FDA-Approved Algorithm Fail to Predict Opioid Use Disorder Risk in Over 450,000 Veterans.

Christal N DavisZeal JinwalaAlexander S HatoumSylvanus ToikumoArpana AgrawalChristopher T RentschHoward J EdenbergJames W BaurleyEmily E HartwellRichard C CristJoshua C GrayAmy C JusticeRachel L KemberHenry R Kranzler
Published in: medRxiv : the preprint server for health sciences (2024)
Candidate genes that comprise the approved algorithm do not meet reasonable standards of efficacy in predicting opioid use disorder risk. Given the algorithm's limited predictive accuracy, its use in clinical care would lead to high rates of false positive and negative findings. More clinically useful models are needed to identify individuals at risk of developing opioid use disorder.
Keyphrases
  • machine learning
  • deep learning
  • healthcare
  • palliative care
  • neural network
  • quality improvement
  • health insurance