Accuracy of automated machine learning in classifying retinal pathologies from ultra-widefield pseudocolour fundus images.

Fares AntakiRazek Georges CoussaGhofril KahwatiKarim HammamjiMikael SebagRenaud Duval

Published in: The British journal of ophthalmology (2021)

AutoML models created by ophthalmologists without coding experience can detect RVO, RP and RD in UWF images with very good diagnostic accuracy. The performance was comparable to bespoke deep-learning models derived by AI experts for RVO and RP but not for RD.

Keyphrases

deep learning
artificial intelligence
machine learning
convolutional neural network
diabetic retinopathy
optical coherence tomography
big data
high resolution
single cell
high throughput