Support Tool for the Presumptive Diagnosis of Glaucoma through Digital Processing of Fundus Images and the Use of Artificial Intelligence (AI)

This project addresses the issue of glaucoma in Ecuador, a neurodegenerative disease that is the second leading cause of blindness worldwide and can lead to irreversible damage due to a lack of timely diagnosis. Given the scarcity of accessible early detection tools, the research proposes the development of a system based on digital processing of biomedical fundus images and Artificial Intelligence (AI) algorithms. The methodology is based on a transdisciplinary approach that combines biomedical signal analysis with machine learning and deep learning techniques. The project has the strategic collaboration of the 'Santa Lucía' Specialty Clinic, allowing for the clinical validation of the developed algorithms and ensuring that the tool meets the necessary medical standards for real-world application. As a result, the project aims to provide a diagnostic support tool that improves the efficiency of early detection, reduces waiting times for patients, and serves as an educational resource for ophthalmology and optometry students. This technological advancement seeks to bridge the gap in access to specialized diagnostics in the country, contributing directly to public health and the well-being of the visually impaired population.<br/><br/><b>Goal</b>: <br/>Develop a support tool for the presumptive diagnosis of glaucoma using digital fundus image processing and Artificial Intelligence. The goal is to facilitate early and accurate detection of this pathology to improve patient prognosis and quality of life.<br/><br/><b>Research lines</b>: <br/>Bioethics and disabilities