8 citations · 8 across the 2 of their papers we have counts for
4 papers
Predicting risk of late age-related macular degeneration using deep learning
Yifan Peng, Tiarnan D. Keenan, Qingyu Chen +5
By 2040, age-related macular degeneration (AMD) will affect approximately 288 million people worldwide. Identifying individuals at high risk of progression to late AMD, the sight-t…
A Simultaneous Inference Procedure to Identify Subgroups from RCTs with Survival Outcomes: Application to Analysis of AMD Progression Studies
Yue Wei, Jason C. Hsu, Wei Chen +2
With the uptake of targeted therapies, instead of the "one-fits-all" approach, modern randomized clinical trials (RCTs) often aim to develop treatments that target a subgroup of pa…
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…
A multi-task deep learning model for the classification of Age-related Macular Degeneration
Qingyu Chen, Yifan Peng, Tiarnan Keenan +5
Age-related Macular Degeneration (AMD) is a leading cause of blindness. Although the Age-Related Eye Disease Study group previously developed a 9-step AMD severity scale for manual…