Solving the Data Challenge in Ophthalmic AI

At ARVO, Cecilia S. Lee, MD, MS, and Aaron Y. Lee, MD, MSCI, discuss barriers to AI deployment in ophthalmology, including interoperability and model development.

By: Cecilia S. Lee, MD, MS, Aaron Y. Lee, MD, MSCI

Ophthalmology Management May 14, 2026

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Cecilia S. Lee

Jane Hardesty Poole Distinguished Professor of Ophthalmology and Visual Science

Affiliations: Washington University in St. Louis

Specialties: Ophthalmology

Bio: Cecilia S. Lee, MD, MS, is the Jane Hardesty Poole Distinguished Professor of Ophthalmology and Visual Science at Washington University in St. Louis. Her work focuses on ophthalmology and vision science, including the use of large data sets and artificial intelligence to advance precision health and ophthalmic research. At ARVO 2026, Dr. Lee and Aaron Y. Lee, MD, MSCI, presented the Cogan Award Lecture, discussing the evolution of data science in ophthalmology and the transition from paper-based clinical records to modern digital research approaches.

Aaron Y. Lee

Specialties: Ophthalmology

Bio: Aaron Y. Lee, MD, MSCI, writes on ophthalmology research at the intersection of retinal imaging, type 2 diabetes, and artificial intelligence. His Retinal Physician article discusses the AI-READI project, an NIH-supported Bridge2AI effort to develop a multimodal, artificial intelligence-ready dataset for diabetes research.

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Ophthalmology Management

Solving the Data Challenge in Ophthalmic AI

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