COMPUTERIZED SYSTEMS FOR PREDICTION OF GEOGRAPHIC ATROPHY PROGRESSION USING DEEP LEARNING APPLIED TO CLINICAL IMAGING

摘要

An electronic device is disclosed. The device receives a plurality of retinal images and patient data corresponding to the retinal images. The device can train a first machine learning model ("model") based on a first group the retinal images and patient data corresponding to the first group and a second model based on a second group of retinal images and patient data corresponding to the second group. The electronic device can generate a first prediction based on the first subset of a third group of retinal images and a second prediction based on the second subset of the third group. After training the first model and the second model, the device can train a third model to predict a geographic atrophy progression in an eye of a patient based on the first and second predictions, the first and second subsets, and patient data corresponding to the first and second subset.