NIHR researchers create A.I. tool to detect retinopathy of prematurity in new-born babies

The study – published last week in The Lancet Digital Health – was conducted by an international team of scientists and supported by the NIHR Moorfields Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology. 

ROP is the leading cause of childhood blindness in wealthy and middle-income countries. As survival rates for premature birth improve globally, its prevalence is likely to increase. The condition already affects up to 30% of premature babies born in sub-Saharan Africa, and while treatment is relatively straightforward, detection rates are low due to the lack of specialist care. This new method of automating ROP diagnosis could help to increase access to treatment around the world and prevent sight loss in thousands of new-born babies. 

The ability of the A.I. tool to work across different ethnicities is particularly significant.  Although currently optimised for the UK population, it has been tested using data from diverse populations in the US, Brazil and Egypt. It has been designed so it can be further optimised for additional populations using data from specific groups or countries. As the tool is ‘code-free’, it can refined by people with little or no coding experience. 

Commenting on the results, first author Dr Siegfried Wagner said:

“We are now further validating our tool in multiple hospitals in the UK, and are seeking to learn how people interact with the A.I.’s outputs to understand how we could incorporate the tool into real-world clinical settings.”