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Fairness and generalisability in deep learning of retinopathy of prematurity screening algorithms: a literature review.

Luis Filipe NakayamaWilliam Greig MitchellLucas Zago RibeiroRobyn Gayle DychiaoWarachaya PhanphrukLeo Anthony CeliKhumbo KaluaAlvina Pauline Dy SantiagoCaio Vinicius Saito RegatieriNilva Simeren Bueno Moraes
Published in: BMJ open ophthalmology (2023)
The reviewed articles included 180 228 images and reported good metrics, but fairness, generalisability and bias control remained limited. Reproducibility is also a critical limitation, with few articles sharing codes and none sharing data. Fair and generalisable ROP and AI studies are needed that include diverse datasets, data and code sharing, collaborative research, and bias control to avoid unpredictable and harmful deployments.
Keyphrases
  • deep learning
  • artificial intelligence
  • health information
  • social media
  • big data
  • convolutional neural network
  • machine learning
  • electronic health record
  • healthcare
  • stress induced
  • rna seq
  • case control
  • single cell