Predicting Age-Related Macular Degeneration Progression with Contrastive Attention and Time-Aware LSTM.

ABSTRACT: Age-related macular degeneration (AMD) is the leading cause of irreversible blindness in developed countries. Identifying patients at high risk of progression to late AMD, the sight-threatening stage, is critical for clinical actions, including medical interventions and timely monitoring. Recently, deep-learning-based models have been developed and achieved superior performance for late AMD prediction. However, most existing methods are limited to the color fundus photography (CFP) from the last ophthalmic visit and do not include the longitudinal CFP history and AMD progression during the previous years' visits. Patients in different AMD subphenotypes might have various speeds of progression in different stages of AMD disease. Capturing the progression information during the previous year

SUBMITTER: Yin C 

PROVIDER: S-EPMC9505703 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature