Deep learning model to identify homonymous defects on automated perimetry.

Aaron Hao Tan Laura DonaldsonLuqmaan MoollaAustin PereiraEdward A Margolin

Published in: The British journal of ophthalmology (2022)

This newly developed deep learning model achieved an overall average accuracy of 87%, making it highly effective in identifying homonymous VF defects on automated perimetry.

Keyphrases

deep learning
artificial intelligence
convolutional neural network
machine learning
high throughput