Detection, prediction, and classification for ocular disease

A computer system comprising:

• a processor;
• a memory in communication with the processor, the memory storing instructions that, when executed by the processor cause the processor to:
• at a training phase,
• receive training data corresponding to a plurality of ocular images, wherein the plurality of ocular images of the training data correspond to a plurality of imaging modalities, said plurality of imaging modalities including delayed near-infrared analysis (DNIRA) and at least one imaging modality other than DNIRA;
• generate delta image data based on a difference between said DNIRA images and images of said at least one imaging modality other than DNIRA;
• perform feature extraction and feature selection to generate features based on the training data and the delta image data to build a pattern recognition model;
• at a classification phase,
• receive a plurality of ocular images corresponding to a plurality of imaging modalities;
• classify features of the plurality of ocular images using the pattern recognition model.