ARTIFICIAL INTELLIGENCE IN EYE DISEASE: AN UPDATE SYSTEMATIC REVIEW

Abstract

Background: In recent years, AI has significantly revolutionized the healthcare industry, with deep learning applications being used to identify various illnesses, evaluate cancerous lesions, and determine stroke onset. AI-based systems also have been applied in ophthalmology to address leading eye diseases. The aim: This study aims to determine the role of artificial intelligence (AI) in eye disease. Methods: By comparing itself to the standards set by the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) 2020, this study was able to show that it met all of the requirements. So, the experts were able to make sure that the study was as up-to-date as it was possible to be. For this search approach, publications that came out between 2014 and 2024 were taken into account. Several different online reference sources, like Pubmed and ScienceDirect, were used to do this. It was decided not to take into account review pieces, works that had already been published, or works that were only half done. Results: In the PubMed database, the results of our search brought up 157 articles, whereas the results of our search on ScienceDirect brought up 256 articles. The results of the search conducted by title screening yielded a total of 34 articles for PubMed and 28 articles for ScienceDirect. We compiled a total of 16 papers, 10 of which came from PubMed and 6 of which came from ScienceDirect. We excluded 4 review articles, 2 non-full text articles, 3 articles having insufficient outcomes, and 1 article having ineligible subjects. In the end, we included six research that met the criteria. Conclusion: Our systematic study suggests that AI has a role in the diagnosis or screening of eye disease. AI can be a valuable tool for diabetic retinopathy (DR) screening, glaucoma screening, myopia screening, and diagnosis of dry eye syndrome.