Artificial intelligence in eye care

Within ophthalmology and optometry, a significant level of diagnostic information is provided in the format of retinal images, involving a range of technologies which include fundus photography, laser scanning ophthalmoscope and optical coherence tomography.

These technologies can provide a unique timeline of the identification and management of ocular disease. There is now, however, increasing interest in using advanced artificial intelligence (AI) techniques to develop diagnostic tools which can function at least as effectively as ‘human’ diagnostic skills. One of the recent landmark events demonstrating the rise of machine intelligence was the success of deep neural networks in mastering the game of Go.¹