Summary
Abstract: This project aims to establish distributed federated learning (FL) approaches for multi-task training of foundational machine learning (ML) models for diabetic retinopathy (DR), using multi-modal, real-world optical coherence tomography (OCT) data (OCT cross-section, OCT angiography (OCTA), and OCT enface). DR is one of the leading causes of severe vision loss. Early detection, prompt intervention, and reliable assessment of treatment outcomes are essential to prevent irreversible vision loss from DR. However, there are major challenges towards developing clinically relevant holistic
