Training artificial intelligence (AI) to recognise red flags in retinal images can help predict if and when people can go on to develop glaucoma — the world’s leading cause of irreversible blindness.
Glaucoma is particularly difficult for doctors to detect, if and when people with suspicious signs of early optic nerve damage. Without the cardinal diagnostic feature of abnormally high internal pressure within the eye — intraocular pressure or IOP for short — it’s hard to predict who will go on to develop glaucoma and risk losing their sight, said researchers from the Seoul National University Hospital in South Korea.
Recent advances in AI have prompted the design of algorithms to better detect glaucoma progression. But none has so far drawn on clinical features to predict disease progression among people at high risk, they pointed out.
“Our results suggest that [deep learning] models that have been trained on both ocular images and clinical data have a potential to predict disease progression in [glaucoma suspect] patients,” said corresponding author Professor Ki Ho Park, from the varsity’s Department of Ophthalmology.
“We believe that with additional training and testing on a larger dataset, our [deep learning] models can be made even better, and that with such models, clinicians would be better equipped to predict individual [glaucoma suspect] patients’ respective disease courses,” Park added.