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Found 5 papers, 1 papers with code
Predicting Risk of Developing Diabetic Retinopathy using Deep Learning
We created and validated two versions of a deep learning system (DLS) to predict the development of mild-or-worse ("Mild+") DR in diabetic patients undergoing DR screening.
Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photos
An algorithm trained on fundus images alone can detect referable GON with higher sensitivity than and comparable specificity to eye care providers.
AmbientGAN: Generative models from lossy measurements
Generative models provide a way to model structure in complex distributions and have been shown to be useful for many tasks of practical interest.
Compressed Sensing using Generative Models
The goal of compressed sensing is to estimate a vector from an underdetermined system of noisy linear measurements, by making use of prior knowledge on the structure of vectors in the relevant domain.
Graphical RNN Models
Many time series are generated by a set of entities that interact with one another over time.
