Detecting Anomalies in Retinal Diseases Using Generative, Discriminative, and Self-supervised Deep Learning

Unsupervised Discovery, Control, and Disentanglement of Semantic Attributes With Applications to Anomaly Detection

(2021) William Paul et al.   NEURAL COMPUTATION

Application of an Anomaly Detection Model to Screen for Ocular Diseases Using Color Retinal Fundus Images: Design and Evaluation Study

(2021) Yong Han et al.   JOURNAL OF MEDICAL INTERNET RESEARCH

Low-Shot Deep Learning of Diabetic Retinopathy With Potential Applications to Address Artificial Intelligence Bias in Retinal Diagnostics and Rare Ophthalmic Diseases

(2020) Philippe Burlina et al.   JAMA Ophthalmology

Assessment of Deep Generative Models for High-Resolution Synthetic Retinal Image Generation of Age-Related Macular Degeneration

(2019) Philippe M. Burlina et al.   JAMA Ophthalmology

AI for medical imaging goes deep

(2018) Daniel S. W. Ting et al.   NATURE MEDICINE

Utility of Deep Learning Methods for Referability Classification of Age-Related Macular Degeneration

(2018) Phillippe Burlina et al.   JAMA Ophthalmology