Artificial intelligence (AI) is reshaping ophthalmology by enhancing diagnostic precision and treatment strategies, particularly in retinal disorders and pediatric ophthalmology. This review examines AI's efficacy in diagnosing conditions such as diabetic retinopathy (DR) and age-related macular degeneration (AMD) using imaging techniques, such as optical coherence tomography (OCT) and fundus photography. AI also shows promise in pediatric care, aiding in the screening of retinopathy of prematurity (ROP) and the management of conditions, including pediatric cataracts and strabismus. However, the integration of AI in ophthalmology presents challenges, including ethical concerns regarding algorithm biases, privacy issues, and limitations in data set quality. Addressing these challenges is crucial to ensure AI's responsible and effective deployment in clinical settings. This review synthesizes current research, underscoring AI's transformative potential in ophthalmology while highlighting critical considerations for its ethical use and technological advancement.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11459419PMC
http://dx.doi.org/10.7759/cureus.71063DOI Listing

Publication Analysis

Top Keywords

artificial intelligence
8
retinal disorders
8
disorders pediatric
8
pediatric ophthalmology
8
review utility
4
utility limitations
4
limitations artificial
4
intelligence retinal
4
pediatric
4
ophthalmology
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!