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HomeminewsAI Breakthrough in Detecting ROP 

AI Breakthrough in Detecting ROP 

A deep learning artificial intelligence (AI) model has been developed that can identify which at-risk infants have retinopathy of prematurity (ROP), according to a recent study. 

The study has been published in the Lancet Digital Health.1 The international research team said it hoped the technique could improve access to screening in the many areas with limited neonatal services and few trained ophthalmologists. 

In a news release from University College London (UCL), lead author Dr Konstantinos Balaskas, from Moorfields Eye Hospital and UCL, said ROP was becoming increasingly common as survival rates of premature babies improve across the globe. 

we hope that our technique to automate diagnostics of ROP will improve access to care in underserved areas and prevent blindness in thousands of newborns worldwide 

Leading Cause of Childhood Blindness 

He said it was now the leading cause of childhood blindness in middle-income countries and in the United States. 

“As many as 30% of newborns in sub-Saharan Africa have some degree of ROP and, while treatments are now readily available, it can cause blindness if not detected and treated quickly. This is often due to a lack of eye care specialists—but, given it is detectable and treatable, no child should be going blind from ROP. 

“As it becomes more common, many areas do not have enough trained ophthalmologists to screen all at-risk children; we hope that our technique to automate diagnostics of ROP will improve access to care in underserved areas and prevent blindness in thousands of newborns worldwide.” 

An estimated 50,000 children worldwide are blind due to ROP. It primarily affects premature babies where abnormal blood vessels grow in the retina. These vessels can leak or bleed, damaging the retina, and possibly leading to retinal detachment.  

While milder forms of ROP only require monitoring, more acute cases require prompt treatment.  

Validity Confirmed 

The deep learning AI model for ROP screening developed by the UCL-Moorfields team was trained on a sample of 7,414 images of newborns’ eyes assessed for ROP by ophthalmologists at Homerton Hospital, London. The hospital serves an ethnically and socioeconomically diverse community, ensuring the tool is safe to use across different ethnic groups.  

The tool’s performance was assessed on 200 images and compared to senior ophthalmologists’ assessments. The tool’s validity was further confirmed by testing it on datasets from the US, Brazil, and Egypt. 

The AI tool was found to be as effective as senior paediatric ophthalmologists in discriminating normal retinal images from those with ROP that could lead to blindness. 


  1. Wagner, S.K., Liefers, B., Radia, M., et al., Development and international validation of custom-engineered and code-free deep-learning models for detection of plus disease in retinopathy of prematurity: a retrospective study, The Lancet Digital Health, 21 April 2023. doi.org/10.1016/S2589-7500(23)00050-X