Mobile app can detect world’s three leading age-related eye disorders

Two university students have developed a mobile app that can detect within seconds if someone is suffering from a range of serious and potentially debilitating age-related eye conditions.

The brainchild of Igor García Atutxa and Francisca Villanueva, the app uses artificial intelligence to analyse a selfie and issue a diagnosis, directing the taker toward the most appropriate medical specialist.

The app can tell if someone is suffering from three of the world’s most common causes of vision loss and blindness – glaucoma, diabetic retinopathy, and cataracts.

The project, dubbed BegIA (begia means ‘eye’ in Basque), has been designed for use in areas of the world where patients face barriers to accessing healthcare.

According to the World Health Organisation (WHO), some 2.2 billion people around the world suffer from some kind of visual impairment or blindness. Half of these cases could have been prevented with early diagnosis.

Francisca Villanueva

Mr García Atutxa and Ms Villanueva, who are both studying on the Master’s Degree in Bioinformatics and Biostatistics at The Open University of Catalonia in Spain (Universitat Oberta de Catalunya), told Agetech World the idea for the app was borne from personal experience.

“A relative suffering from type 2 diabetes began to lose a great deal of sight, to the point that they could no longer drive or read,” explained Mr García Atutxa. “They developed diabetic retinopathy, an eye disease that causes vision loss and whose impact can be reduced with early diagnosis.”

Early diagnosis requires an examination of the back of the eye by an ophthalmology specialist using the correct optical instruments.

But while those living in developed countries and urban areas can usually easily access such services, it can be a major problem for those in rural locations and less advanced regions of the world.

In response Mr García Atutxa, a physicist working in data analysis, and Ms Villanueva, a biochemist specialising in degenerative diseases, developed the pioneering technology that’s able to provide an ophthalmic pre-diagnosis that can distinguish between different diseases at once.

BegIA uses a neural network artificial intelligence algorithm able to leverage deep learning techniques to recognise, by means of a frontal mobile selfie, whether the subject has an eye disease.

Having developed the algorithm, which the pair trained using images supplied by Mexico’s Instituto Tecnológico y de Estudios Superiores de Monterrey, at which Ms Villanueva is a researcher, Mr Garcia Atutxa said they are now “in talks with hospitals and diabetes associations to secure images with greater variability, which will help us to train our algorithm better.”

The app, which follows the principles of the WHO’s VISION 2020 project for the prevention of blindness, has already won the Ramon Molinas Foundation Prize for Social Impact at the 2023 SpinUOC, an Open University of Catalonia entrepreneurship and knowledge transfer programme organised by Hubbik, a mentoring platform for start-ups and spin-offs.

The app’s creators estimate it could be on the market within two years.

The images they have used are of patients with retinopathy, glaucoma or cataracts. What the algorithm does is use calculations to fit the result to the image in question. Mr Garcia Atutxa said: “The more images we get, the more robust our algorithm becomes.”

In addition to the algorithm, the UOC master’s degree students have also created an initial version of the mobile app for Android.

“We entered SpinUOC because we wanted to develop a more sophisticated app that, in addition to detecting diseases, had more functions and could work on any mobile phone with limited computational capacity,” explained Ms Villanueva.

The BegIA mobile app is aimed at both the medical community and potential patients.

In addition to early diagnosis of ophthalmological conditions, it will allow for remote medical monitoring.

Once a doctor has made a diagnosis and set up a treatment plan for someone, they will be able to track its effectiveness and the evolution of the condition via images taken with the app, with no need for the patient to travel and invest large sums of money in ongoing medical care.