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Fairness and generalizability of OCT normative databases: a comparative analysis.

Luis Filipe NakayamaLucas Zago RibeiroJuliana Angelica Estevão de OliveiraJoão Carlos Ramos Gonçalves de MatosWilliam Greig MitchellFernando Korn MalerbiLeo Anthony CeliCaio Vinicius Saito Regatieri
Published in: International journal of retina and vitreous (2023)
In all analyzed databases, the data framework is static, with limited upgrade options and lacking normative databases for new modules. As a result, caution in OCT normality interpretation is warranted. To address these limitations, there is a need for more diverse, representative, and open-access datasets that take into account patient demographics, especially considering the development of supervised Machine Learning algorithms in healthcare.
Keyphrases
  • machine learning
  • big data
  • artificial intelligence
  • healthcare
  • optical coherence tomography
  • diabetic retinopathy
  • deep learning
  • minimally invasive
  • case report
  • cross sectional
  • optic nerve
  • electronic health record