Estimating the prevalence of diabetic retinopathy in electronic health records with massive missing labels

Research output: Contribution to journalArticlepeer-review

Original languageEnglish
Article number100154
JournalIntelligence-Based Medicine
Volume10
DOIs
StatePublished - Jan 2024

ASJC Scopus Subject Areas

  • Medicine (miscellaneous)
  • Health Informatics
  • Computer Science Applications
  • Artificial Intelligence

Keywords

  • Bayesian mixture models
  • Classification
  • Diabetic retinopathy
  • Machine learning
  • Positive-unlabeled learning
  • Predictive inference

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