Abstract

Optical Coherence Tomography (OCT) proves essential as an imaging modality for detecting early diseases especially by helping patients who age and face increased susceptibility to retinal and systemic conditions. The development of artificial intelligence technology now boosts OCT diagnostic features to identify conditions like diabetic retinopathy in addition to age-related macular degeneration and cardiovascular diseases at an early stage. This paper examines two main advancements in artificial intelligence for OCT imaging monitoring such as Google Health's Retinal Disease Predictor and AI systems used to evaluate cardiovascular risks. This research develops HealthSight AI which combines deep learning algorithms with real-time predictive analytics to detect multiple diseases in healthcare. Medical studies demonstrate how AI-enhanced OCT technology can transform preventive healthcare delivery through its clinical implementations. The integration of AI in OCT imaging holds vast prospective advantages yet operational hurdles stem from ethical matters and system adherence needs together with healthcare structure implementation barriers. The findings emphasize the necessity to develop additional research together with collaboration so AI-powered OCT imaging can reach broad clinical implementation.