Login / Signup

Performance and Limitation of Machine Learning Algorithms for Diabetic Retinopathy Screening: Meta-analysis.

Jo-Hsuan WuT Y Alvin LiuWan-Ting HsuJennifer Hui-Chun HoChien-Chang Lee
Published in: Journal of medical Internet research (2021)
This meta-analysis demonstrated high diagnostic accuracy of ML algorithms in detecting DR on color fundus photographs, suggesting that state-of-the-art, ML-based DR screening algorithms are likely ready for clinical applications. However, a significant portion of the earlier published studies had methodology flaws, such as the lack of external validation and presence of spectrum bias. The results of these studies should be interpreted with caution.
Keyphrases
  • machine learning
  • diabetic retinopathy
  • case control
  • systematic review
  • meta analyses
  • artificial intelligence
  • deep learning
  • optical coherence tomography
  • big data
  • editorial comment