Area of research
Ophthalmology · Radiology, Nuclear Medicine and Imaging
Research interest
Research interests include Retinal Imaging and Analysis, Retinal Diseases and Treatments, Glaucoma and retinal disorders, and Retinal and Optic Conditions.
Diabetic Retinal Disease Cure Accelerator: Modernizing Staging and Endpoints
Cost-effectiveness of AI for pediatric diabetic eye exams from a health system perspective.
Evaluating commercial multimodal AI for diabetic eye screening and implications for an alternative regulatory pathway.
Progressive inner retinal neurodegeneration in non-proliferative macular telangiectasia type 2.
Autonomous artificial intelligence increases screening and follow-up for diabetic retinopathy in youth: the ACCESS randomized control trial.
Scaling Adoption of Medical AI — Reimbursement from Value-Based Care and Fee-for-Service Perspectives
Autonomous artificial intelligence for diabetic eye disease increases access and health equity in underserved populations.
A New Approach to Staging Diabetic Eye Disease: Staging of Diabetic Retinal Neurodegeneration and Diabetic Macular Edema.
Ethical Considerations in the Design and Conduct of Clinical Trials of Artificial Intelligence.
Clinical Implementation of Autonomous Artificial Intelligence Systems for Diabetic Eye Exams: Considerations for Success.
Mitigation of AI adoption bias through an improved autonomous AI system for diabetic retinal disease.
Autonomous Artificial Intelligence Increases Access and Health Equity in Underserved Populations with Diabetes
Risk Factors for Nondiagnostic Imaging in a Real-World Deployment of Artificial Intelligence Diabetic Retinal Examinations in an Integrated Healthcare System: Maximizing Workflow Efficiency Through Predictive Dilation.
What Do We Do with Physicians When Autonomous AI-Enabled Workflow is Better for Patient Outcomes?
Author Correction: Autonomous artificial intelligence for diabetic eye disease increases access and health equity in underserved populations.
Sterile Caliper Anterior Chamber Decompression Mitigates Intraocular Pressure Spikes in Intravitreal Injections.
Autonomous AI for diabetic eye disease at primary care improves ophthalmic access for at-risk patients
Considerations for addressing bias in artificial intelligence for health equity
Considerations for addressing bias in artificial intelligence for health equity.
Generative Artificial Intelligence Through ChatGPT and Other Large Language Models in Ophthalmology
Autonomous artificial intelligence increases real-world specialist clinic productivity in a cluster-randomized trial
Generative Artificial Intelligence Through ChatGPT and Other Large Language Models in Ophthalmology: Clinical Applications and Challenges.
Autonomous artificial intelligence increases real-world specialist clinic productivity in a cluster-randomized trial.
Autonomous AI systems in the face of liability, regulations and costs.
A New Approach to Staging Diabetic Eye Disease
Effectiveness of artificial intelligence screening in preventing vision loss from diabetes: a policy model.
The Definition of Glaucomatous Optic Neuropathy in Artificial Intelligence Research and Clinical Applications.
Evaluation of retinal nerve fibre layer thickness as a possible measure of diabetic retinal neurodegeneration in the EPIC-Norfolk Eye Study.
Is the Algorithm Good in a Bad World, or Has It Learned to be Bad? The Ethical Challenges of "Locked" Versus "Continuously Learning" and "Autonomous" Versus "Assistive" AI Tools in Healthcare.
Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI.