Work

The Advent of Big Data and Machine Learning in Ophthalmology: The 2026 Cogan Lecture

Year: 2026

Type: article

Abstract: The major objective of this lecture is to summarize the evolution of computational ophthalmology over the past 2 decades through the scientific advances that have transformed ophthalmic research. Topics include the emergence of computational ophthalmology, the role of big data in scientific discovery, the application of machine learning to ophthalmic imaging, and the development of artificial intelligence (AI)-ready data ecosystems. The lecture concludes by exploring the next frontier in computational ophthalmology, highlighting foundation models and agentic AI as emerging approaches with the potential to accelerate scientific discovery, and improve clinical care are discussed. This article is based on the 2026 Cogan Award Lecture presented by Aaron Y. Lee, MD, MSCI, and Cecilia S. Lee, MD, MS, at ARVO 2026.

Source: Investigative Ophthalmology & Visual Science

DOI: 10.1167/iovs.67.12.72

Authors: Scott Song, Aaron Y. Lee, Cecilia S. Lee

Institution: Washington University in St. Louis

Language: English

Topic: Retinal Imaging and Analysis

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

Open Access status: gold

Estimated APC paid: $1,850