Science and Research
Artificial intelligence research
CERA scientists are at the forefront of artificial intelligence research, developing and applying innovative technologies to detect and better understand eye disease.
Overview
Artificial intelligence – computer programs that are trained to learn and complete tasks that would usually require human intelligence – is playing an increasingly significant role in research innovation at CERA.
Powerful imaging technologies combined with deep learning algorithms are transforming our ability to screen for eye diseases, with some new tools now able to analyse images of the retina at least as well as doctors.
One of CERA’s key projects is the development of an AI-powered screening tool capable of detecting early signs of common eye diseases — such as age-related macular degeneration, diabetic retinopathy, glaucoma and keratoconus — within seconds and with high accuracy. This technology could enable preliminary eye health assessments to be conducted in a broader range of healthcare settings, including general practice clinics and by healthcare workers in remote communities.
Recognising that the eye is a window to the body, CERA researchers are also harnessing AI to predict the risk of systemic diseases —including cardiovascular disease, Alzheimer’s disease and kidney disease — through analysis of retinal images. These images are non-invasive, quick, affordable and widely accessible, offering a unique opportunity to screen for multiple systemic conditions. This approach supports earlier detection and prevention, ultimately aiming to improve health outcomes across diverse populations.
Why this research is important
Artificial intelligence is changing the future landscape of medicine and medical research, and ophthalmology is at the forefront.
CERA researchers are demonstrating that AI technologies have the potential to make eye screening more accessible and convenient for patients, and to help doctors predict the progression of eye disease.
This could allow for more cost-effective care, reduce stressful workloads for clinicians, and provide more flexibility and empowerment for patients. It can also play a vital role in helping to close the gap in eye health care, bringing services to remote communities where access to eye specialists is often scarce.