Revolutionizing Eye Disease Treatment with AI, Machine Learning, and Deep Learning: Recent Advances in Eye Health

Abstract

Objective: Vision-related ailments impacting retinal structures, as well as glaucoma, cataracts, and diabetic retinopathy, are major contributors to blindness globally. Recent breakthroughs in Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) provide encouraging options for the early identification, diagnosis, and management of these illnesses. This article examines current studies regarding the applications of AI, ML, and DL in the field of ophthalmology, focusing on their influence on the treatment of eye diseases and the accuracy of diagnoses.

Methods: An extensive review of pertinent research articles published from 2018 to 2024 was conducted by searching databases such as PubMed, IEEE Xplore, and Scopus. The analysis focused on studies investigating the role of artificial intelligence in diagnosing eye diseases, including aspects of detection and management.

Results: Studies show that ophthalmology has made significant progress with artificial intelligence, machine learning, and deep learning technologies that are particularly effective at assessing diagnostic images. These technologies yield high-quality results in the diagnosis of retinal diseases, glaucoma, cataracts, and various other eye conditions by analyzing retinal images, fundus photographs, and optical coherence tomography (OCT) scans. AI-driven decision support systems assist healthcare professionals in creating tailored treatment plans for individual patients, leading to improved outcomes for patients.

Conclusion: The main advantages for patients from AI, ML, and DL technologies encompass precise medical diagnosis abilities, along with controlled pathology identification and tailored healthcare treatment solutions. These advanced technologies function amidst challenges related to data quality, interpretative complexities, and ethical issues, yet they are poised to bring significant enhancements to the management of eye healthcare. Research needs to tackle the existing challenges so that AI can achieve its full potential as a fundamental component of medical practice.