Using Artificial Intelligence to predict AMD progression

Pearse Keane looking into a microscope

Pearse Keane, UCL and Moorfields Eye Hospital - £126,462

This project aims to use the power of computers and artificial intelligence to better understand age-related macular degeneration (AMD). Using eye scans from patients with wet and dry AMD the researchers want to better understand why and how AMD develops and what causes the progression from dry AMD to wet AMD.

What is the problem?

Dry AMD is a slow progressing disease, which can lead to wet AMD and more rapid sight loss. It is difficult to know which patients will develop wet AMD. Dry AMD patients are encouraged to self-monitor their sight for changes. We know that the quicker we can treat wet AMD the more sight can be maintained. So, it is important to be able to predict and monitor for the start of wet AMD.

What are they doing?

Researchers are analysing an incredibly large database of AMD eye scans using artificial intelligence. Using scans of different patients Dr Pearse Keane and his team are trying to understand the progression from dry to wet AMD. They also will analyse how wet AMD treatments affect the retina over time.

How can this help?

Better understanding the development of wet AMD may allow patients at high risk to be monitored more closely. And their wet AMD picked up and treated earlier. This could mean these patients maintain more of their vision.

It will also help us understand how different treatments for wet AMD differ in terms of their effects on the retina. In particular, it will provide new insights into scarring of the macula and how dry AMD progresses alongside wet AMD. 

All the data and results of the analyses will be made available to other researchers around the world for them to use in their research. This helps research grow and progress.

Professor Luminita Paraoan and her team, University of Liverpool

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Since 1987 the Macular Society has invested around £10 million in over 100 research projects.

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