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Toward safer ophthalmic artificial intelligence via distributed validation on real-world data.

Siddharth Nath¹, Ehsan Rahimy², Ashley Kras^3,4

¹Department of Ophthalmology and Visual Sciences, McGill University, Montréal, Québec, Canada.

Current Opinion in Ophthalmology

|July 17, 2023

Summary

Algorithm validation in ophthalmology is crucial for safe clinical use. Developing a consensus approach for machine learning tools is urgently needed to ensure reliable implementation.

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Area of Science:

Ophthalmology
Machine Learning
Medical Informatics

Background:

Numerous machine learning applications have been developed for ophthalmic diagnosis and monitoring.
Despite extensive datasets, few algorithms achieve regulatory approval for clinical practice.

Conclusions:

There is an urgent need for a consensus approach to algorithm validation.
Collaboration between developers, researchers, and clinicians is essential for safe and equitable implementation of machine learning in ophthalmology.