Artificial intelligence in cornea and ocular surface diseases

Luca Pagano; Matteo Posarelli; Giuseppe Giannaccare; Giulia Coco; Vincenzo Scorcia; Vito Romano; Alfredo Borgia

doi:10.4103/sjopt.sjopt_52_23

Artificial intelligence in cornea and ocular surface diseases

Saudi J Ophthalmol. 2023 Sep 16;37(3):179-184. doi: 10.4103/sjopt.sjopt_52_23. eCollection 2023 Jul-Sep.

Authors

Luca Pagano¹, Matteo Posarelli¹, Giuseppe Giannaccare², Giulia Coco³, Vincenzo Scorcia², Vito Romano⁴, Alfredo Borgia^{1

5}

Affiliations

¹ Cornea Service, St. Paul's Eye Unit, Royal Liverpool University Hospital, Liverpool, UK.
² Department of Ophthalmology, University "Magna Græcia" of Catanzaro, Catanzaro.
³ Department of Clinical Science and Translational Medicine, University of Rome Tor Vergata, Rome.
⁴ Department of Medical and Surgical Specialties, Radiological Sciences, and Public Health, Ophthalmology Clinic, University of Brescia, Brescia.
⁵ Eye Clinic, Humanitas Gradenigo, Turin, Italy.

Abstract

In modern ophthalmology, the advent of artificial intelligence (AI) is gradually showing promising results. The application of complex algorithms to machine and deep learning has the potential to improve the diagnosis of various corneal and ocular surface diseases, customize the treatment, and enhance patient outcomes. Moreover, the use of AI can ameliorate the efficiency of the health-care system by providing more accurate results, reducing the workload of ophthalmologists, allowing the analysis of a big amount of data, and reducing the time and resources required for manual image acquisition and analysis. In this article, we reviewed the most important and recently published applications of AI in the field of cornea and ocular surface diseases, with a particular focus on keratoconus, infectious keratitis, corneal transplants, and the use of in vivo confocal microscopy.

Keywords: Artificial intelligence; cornea; dry eye disease; keratoconus; ocular surface.