A Deep-Learning-Driven Remote Endoscopy Video Diagnostic Support System to Improve Early Gastrointestinal Disease Detection

Building on these findings, this project aims to develop a proof-of-concept framework for an AI-driven remote endoscopy video interpretation system to enhance early detection and support clinical decision. The goal is to create the foundation for a system that can assist clinicians by identifying suspicious regions, offering preliminary decision cues, and facilitating remote specialist collaboration where needed. This collaboration will involve clinicians and researchers in NI, Tunisia, Uzbekistan and Pakistan, ensuring that the system is adapted to local diagnostic pathways, equipment constraints, and infrastructural realities.