Glaucoma Diagnosis through AI-Generated Insights: A Dual Modality Perspective - OCT vs Fundus

Capstone Project · Yoobee College

Glaucoma is a progressive optic nerve disease and a leading cause of blindness worldwide. Early and accurate diagnosis is critical to preventing vision loss. Recent advances in AI, deep learning, and generative models have significantly improved automated glaucoma detection through retinal imaging. This review examines current trends and future directions in AI-driven glaucoma diagnosis, with a focus on multimodal imaging using fundus photography and Optical Coherence Tomography (OCT). It highlights limitations of existing models, explores generative AI techniques, and discusses how combining fundus and OCT imaging can boost diagnostic accuracy. Key challenges including clinical translation, data limitations, and model interpretability are addressed, along with future pathways toward more robust, explainable, and equitable AI in ophthalmology.

ADOPTION OF DATA ANALYTICS TOOLS FOR DECISION MAKING OF RETAIL BUSINESS IN NEPAL

Thesis

This research study sheds light on the evolving landscape of decisionmaking in the retail sector, particularly within the context of the dynamic and competitive environment of e-commerce in Nepal. The insights gained from this study provide valuable information for retailers, policymakers and industry stakeholders looking to harness the potential of data analytics tools to drive effective decisionmaking processes in the retail business. The findings underscore the importance of embracing online analytical processing and advanced analytics while also suggesting that further exploration is needed to unlock the full potential of data warehousing and data marts in the retail sector.