A mobile app capable of early detection of glaucoma, diabetic retinopathy, and cataracts has been designed for use in parts of the world lacking easy access to healthcare.
The project is the work of two students on the Master’s Degree in Bioinformatics and Biostatistics at the Universitat Oberta de Catalunya (UOC) as well as García Atutxa, a physicist specialising in data analysis, and Francisca Villanueva-Flores, a biochemist specialising in degenerative diseases.
Dubbed BegIA (begia means ‘eye’ in Basque), the app uses artificial intelligence (AI) to analyse a selfie and issue a diagnosis that, if positive, directs its taker towards the most appropriate medical specialist. In addition to early diagnosis of ophthalmological conditions, it will allow for remote medical monitoring.
Once a diagnosis has been made and a treatment plan set up, images taken with the app can be used to track disease progression, with no need for the patient to travel.
BegIA uses a neural network AI algorithm able to leverage deep learning techniques to recognise, in a frontal image of the face taken by means of a mobile selfie, whether the subject has an eye disease within “a matter of seconds”.
The algorithm was trained using images supplied by Mexico’s Instituto Tecnológico y de Estudios Superiores de Monterrey, and the students are now in discussion with hospitals and diabetes associations to secure images with greater variability.