Area of research
Artificial Intelligence · Radiology, Nuclear Medicine and Imaging
Research interest
Research interests include Retinal Imaging and Analysis, Adversarial Robustness in Machine Learning, Retinal Diseases and Treatments, and Remote-Sensing Image Classification.
Addressing Artificial Intelligence Bias in Retinal Diagnostics
Deep learning in ophthalmology: The technical and clinical considerations
Assessment of Deep Generative Models for High-Resolution Synthetic Retinal Image Generation of Age-Related Macular Degeneration
AI for medical imaging goes deep
Use of Deep Learning for Detailed Severity Characterization and Estimation of 5-Year Risk Among Patients With Age-Related Macular Degeneration
Automated Grading of Age-Related Macular Degeneration From Color Fundus Images Using Deep Convolutional Neural Networks
Comparing humans and deep learning performance for grading AMD: A study in using universal deep features and transfer learning for automated AMD analysis
Automated diagnosis of myositis from muscle ultrasound: Exploring the use of machine learning and deep learning methods
Validating Retinal Fundus Image Analysis Algorithms: Issues and a Proposal