most citedDeepSeeNet: A deep learning model for automated classification of patient-based age-related macular degeneration severity from color fundus photographs

368 citations · 383 across the 3 of their papers we have counts for

collaborators
Showing eess.IVShow all

1 paper · 1 filter

eess.IV2019

A deep learning approach for automated detection of geographic atrophy from color fundus photographs

Tiarnan D. Keenan, Shazia Dharssi, Yifan Peng +5

Purpose: To assess the utility of deep learning in the detection of geographic atrophy (GA) from color fundus photographs; secondary aim to explore potential utility in detecting c…