Using artificial intelligence to monitor the progression of scleroderma and psoriatic arthritis
Disease - Systemic sclerosis (scleroderma) and Psoriatic arthritis
Lead applicant - Dr Francesco Del Galdo
Organisation - University of Leeds
Type of grant - Med Tech POC 2019
Status of grant - Active
Amount of the original award - £89,999.09
Start date - 01 October 2019
Reference - 22413
Public Summary
What are the aims of this research?
Systemic sclerosis (scleroderma) and psoriatic arthritis are conditions that can affect some people who have already been diagnosed with Raynaud’s phenomenon or psoriasis, respectively.
This research aims to use artificial intelligence to look at the progression of Raynaud’s phenomenon or psoriasis, into scleroderma or psoriatic arthritis, using photographs uploaded by patients directly from their mobile phones.
Why is this research important?
Many people with scleroderma or psoriatic arthritis wait a long time for a diagnosis, which can lead to worsened symptoms and outcomes. To address this, researchers are trying to work out how we can diagnose, and therefore treat these conditions earlier.
This project will create mobile-based technology to process photographs uploaded by patients. This will involve training a computer system to identify signs of the progression of Raynaud’s phenomenon and psoriasis, into scleroderma and psoriatic arthritis. The findings from the photographs will be confirmed using other tests such as MRI, DNA and blood tests.
How will the findings benefit patients?
The development of this technology ultimately aims to predict the development of scleroderma and psoriatic arthritis, leading to earlier and more accurate diagnoses, and therefore better outcomes for patients.
It hopes to empower patients and better engage them in the screening of their symptoms, and aid doctor’s assessments without increasing demands on the NHS.
This grant is co-funded with the Medical Research Council and The Kennedy Trust, and managed by Medical Technologies Innovation and Knowledge Centre (IKC).