New AI tool helps spot cataracts in babies

A cutting-edge collaboration is reshaping how newborns are screened for vision problems, offering hope for earlier and more accurate diagnoses across the globe.
Baby

A groundbreaking medical device designed to detect cataracts in newborns is being enhanced with the help of AI. The Neocam, a handheld digital imaging tool created by Addenbrooke’s eye surgeon, Dr Louise Allen, allows midwives to take photos of a baby’s eyes to spot congenital cataracts — the leading cause of preventable childhood blindness.

A new AI feature under development will instantly assess whether a photo is clear enough for diagnosis, streamlining the process and reducing the need for retakes. The improvements are being developed by Cambridgeshire-based consultancy 42 Technology (42T), whose software engineers train a machine-learning model using a vast dataset of 46,000 anonymised images.

The AI project is backed by an innovation grant from Addenbrooke’s Charitable Trust (ACT) to make Neocam more accurate and accessible, especially in areas with limited specialist care. Neocam is currently being trialled in maternity units across the UK as part of a large-scale study called DIvO, where over 140,000 babies will have their eyes screened using both traditional methods and the new device.

Although the final results are not expected until 2027, early findings suggest Neocam has already identified rare visual conditions that would have otherwise gone undetected. Dr Allen emphasised the importance of collaboration and public support for the project, saying that the AI-enhanced Neocam could make early detection of eye conditions more reliable worldwide.

Why does it matter?

With growing support from institutions like the National Institute for Health and Care Research and ACT, this innovation could significantly improve childhood eye care across both urban and remote settings.

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