Machine learning in neovascular age-related macular degeneration

Study code
DAA061

Lead researcher
Konstantinos Balaskas

Study type
Data only

Institution or company
Moorfields Eye Hospital NHS Foundation Trust

Speciality area
Ophthalmology, Genomics and Rare Diseases

Summary

Age-related Macular Degeneration is the main cause of vision loss in the UK. Although there are effective treatments in the form of eye injections, there are many factors affecting how well patients respond to these treatments. Not all these factors are well understood and especially how they interact with each other and how this can help predict treatment response. The main three sources of information that can help clinicians predict response to treatment and adjust the treatment regimen to the specific needs of each patient are: clinical information (such as age, vision), details from imaging tests (such as optical coherence tomography) and the genetic make-up of each patient. Novel methods of artificial intelligence for analysing complex information can help make sense of all this data and single out the factors that can help tailor treatments to the needs of each patient. In this project we will combine clinical, imaging and genetic information from patients already attending Moorfields clinics for treatment of Neovascular AMD (nAMD) treated with injections. We will use novel artificial intelligence methods for analysing images and exporting detailed information from them so that we can ‘personalise’ our treatments for patients with nAMD and give accurate predictions for the outcomes of treatment in terms of vision.