An international group of researchers has successfully applied artificial intelligence (AI) technology to real-world retinal imagery to detect possible diseases more accurately and on a larger scale.

Retinal examinations can detect a number of diseases that affect the eye. Fundus photography is a process of taking photographs of the interior of the eye through the pupil and is a way to screen and monitor such retinal diseases.

The introduction of AI technology to fundus photography has improved the platform and enabled it to detect and monitor retinal diseases on a large scale.

The Comprehensive AI Retinal Expert (CARE) system has been developed by an international group of researchers from Sun Yat-sen University, Beijing Eaglevision Technology (Airdoc), Monash University, University of Miami Miller School of Medicine, Beijing Tongren Eye Centre and Capital Medical University.

As reported by Monash University in Australia, the researchers expect that CARE would be adopted in medical settings across China and later in the Asia Pacific (APAC) region.

The research will also build out a database of screening images from real-world environments that can be rolled out in clinical settings to better diagnose retinal diseases.