Artificial Intelligence in Cornea, Refractive, and Cataract Surgery

Aazim A. Siddiqui; John G. Ladas; Jimmy K. Lee

Disclosures

Curr Opin Ophthalmol. 2020;31(4):253-260. 

In This Article

Artificial Intelligence and Ophthalmology

In the recent years, artificial intelligence has already found areas of broad applications within ophthalmology. It is being integrated into fundus photography, optical coherence tomography, and visual field testing.[3] This has led to the advancement of efficient and accurate screening, grading, and management of various retinal disorders. These include retinopathy of prematurity, age-related macular degeneration, and diabetic retinopathy. Furthermore, in glaucoma, this technology has helped with the screening and detection of early glaucomatous disease.[3,4] The ability to perform these tasks remotely with the help of artificial intelligence and its deep learning capabilities can also make an impact through telemedicine especially in developing countries.[4,5]

In a general sense, artificial intelligence operates by learning the relationship of multiple complex variables from a large data set and weighing them accordingly as they relate to a specific outcome. This is useful in identifying patterns of a diagnostic criteria, making management decisions, scoring a prognosis, or performing automation for laborious tasks.[4,5] Artificial intelligence is a dynamic solution, which continues to grow and improve as the training data set becomes larger. Its strength is in its scalability, flexibility, and malleability to include additional variables and complexities.

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