<![CDATA[Artificial intelligence (AI) has come a long way since its introduction in the 1950s. In the past few decades, especially with the advent of machine learning (ML) and deep learning (DL), AI has been able to analyze complex data, learn independently, and have made a major impact on the medical field. Ophthalmology has been one of the major beneficiaries of this technology, thanks to its integration with digital techniques such as Optical Coherence Tomography (OCT), fundus photography, and visual field testing. This study was conducted through a comprehensive literature review using major databases, such as PubMed, Scopus, and Google Scholar. Inclusion criteria included publications in the last five years that were relevant to innovations in AI-based diagnostics and management of eye diseases. A total of 25 journals were selected for analysis, providing insight into the current trends in AI applications for ophthalmology. We found that AI has provided efficiencies in the diagnosis, treatment, and management of eye diseases, as well as expanded access to healthcare through telemedicine. However, challenges such as data validation and algorithm standardization require attention. Through cross-disciplinary collaboration and further development, AI has the potential to revolutionize ophthalmology services to be more inclusive and affordable.]]>
Copyrights © 2025
