Skip to main content
Research project

Deciphering AMD by Deep Phenotyping and Machine Learning- Prospective Study (PINNACLE)

  • Research groups:
  • Lead researcher:
  • Research funder:
    National Institute of Health and Care Research
  • Status:

Project overview

Age-related-macular-degeneration (AMD) is a very common cause of blindness. Unfortunately, doctors don’t know who will progress to the sight threatening stage of the disease. Some patients progress slowly or not at all and others quickly. We can teach computers to analyse high resolution images of the inside of the eye. We have access to hundreds of thousands of such images from patients with AMD and patients who don’t have AMD. These images allow us to train computers to identify what eye changes appear in patients with AMD. Once the computers have learnt this, we expect they will identify new changes we haven’t thought of. Using this approach we think we will be able to better predict which patients will progress. This should help us develop better treatments and enter the most appropriate patients into clinical trials. It should allow us to better understand why AMD develops too.


Lead researcher

Professor Andrew Lotery

Professor of Ophthalmology

Research interests

  • Ocular clinical trials
  • Age related macular degeneration
  • Central serous chorioretinopathy

Collaborating research institutes, centres and groups

Research outputs

Rebecca Kaye,
Karina Patasova,
Praveen J. Patel,
Pirro Hysi,
, 2021 , Scientific Reports , 11
Type: article
Ahmed M. Hagag,
Shruti Chandra,
Hagar Khalid,
Ali Lamin,
Pearse A. Keane,
& Sobha Sivaprasad
, 2020 , Journal of Clinical Medicine , 9 (6)
Type: article
to top