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Peer-reviewedCC BY-NC-ND 4.0Investigative Ophthalmology & Visual Science

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

  • Scott Song1
  • Aaron Y. Lee1
  • Cecilia S. Lee1
  1. 1John F. Hardesty Department of Ophthalmology and Visual Sciences, Washington University in St. Louis, St. Louis, Missouri, United States
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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.

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Cite

BibTeXRIS
BibTeX
@article{song2026advent,
  title = {{The Advent of Big Data and Machine Learning in Ophthalmology: The 2026 Cogan Lecture}},
  author = {Scott Song and Aaron Y. Lee and Cecilia S. Lee},
  journal = {Investigative Ophthalmology \& Visual Science},
  year = {2026},
  month = oct,
  doi = {10.1167/iovs.67.12.72},
  url = {https://doi.org/10.1167/iovs.67.12.72},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - JOUR
TI  - The Advent of Big Data and Machine Learning in Ophthalmology: The 2026 Cogan Lecture
AU  - Scott Song
AU  - Aaron Y. Lee
AU  - Cecilia S. Lee
PY  - 2026
DA  - 2026/10/28
JO  - Investigative Ophthalmology & Visual Science
DO  - 10.1167/iovs.67.12.72
UR  - https://doi.org/10.1167/iovs.67.12.72
AB  - 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.
SN  - 0146-0404
SN  - 1552-5783
ER  -