Advancements in Eye Disease Management Using Artificial Intelligence, Machine Learning, and Deep Learning: Recent Research in Eye Health
Abstract
Eye diseases that affect retina structures along with glaucoma and cataracts and diabetic retinopathy represent significant causes of blindness throughout the world. Recent advancements in Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) offer promising solutions for the early detection, diagnosis, and management of these conditions. The article analyses contemporary research about AI along with ML and DL applications in ophthalmology with attention to their effects on eye disease treatment and diagnostic precision.
Methods:
A thorough analysis of relevant research papers between 2018 and 2024 took place through database searches in PubMed along with IEEE Xplore and Scopus. The research analysis included research which studied artificial intelligence-based diagnostics of eye diseases including their detection and management roles.
Results: Research indicates that ophthalmology has achieved notable advances with AI, ML and DL technologies which excel at analyzing diagnostic images. Quality results in diagnosing retinal diseases along with glaucoma and cataract as well as multiple eye conditions through the analysis of retinal images and fundus photographs alongside optical coherence tomography (OCT) scans. Through AI-operated decision support platforms medical professionals receive aid in designing treatment plans customized for specific patients which results in better patient success.
Conclusion: The primary benefits for customers from AI and ML and DL technologies include exact medical diagnosis capabilities along with managed pathology recognition and individualized healthcare treatment options. The advanced technologies operate with data quality limitations and interpretive complexities and ethical concerns yet will produce remarkable improvements to eye health care administration. Research must address existing problems in order for AI to reach its full potential as a standard medical practice element
