Skin Analytics uses AI algorithms that can take a dermoscopic image of a skin lesion helping to identify skin cancer.
Skin Analytics uses AI algorithms that can take a dermoscopic image of a skin lesion helping to identify skin cancer.
“Two-week rule referrals place an enormous burden on Dermatology services across the UK. However, typically fewer than 10% of such referrals turn out to have a significant skin cancer. Teledermatology offers the potential to greatly improve the current referral pathway and ensure that patients with skin cancer receive care, in both a quick and efficient manner.”
Niall Wilson, Skin Analytics Medical Director and consultant Dermatologist, Broadgreen Hospital
Summary:
By enabling dermatologist-quality screening in Primary Care within current appointment times and without the need for expensive equipment, Skin Analytics’ solution
supports:
GP practices are provided with a dermascope and image capture device. This can be used during a consultation to capture an image of any pigmented lesions a GP would select for referral. An artificial intelligence (AI) algorithm identifies: suspected melanoma, common types of nonmelanoma skin cancer, benign (noncancerous) lesions.
Challenge/problem identified:
Some areas of the UK have 0.64 dermatologists per 100,000 population, compared to the Royal College of Physicians recommendation of 1.6.
Skin Analytics’ solution can therefore relieve pressure on a specialism which in 2014 required more than 13 million GP appointments*.
Anecdotal evidence provided by Skin Analytics’ dermatologist partners suggests that over 90% of two-week referrals they receive are in the wrong patient pathway. By providing an accurate way to stratify referrals by suspect melanoma and suspect nonmelanoma skin cancers, GPs are empowered to refer through the appropriate channel,
thereby reducing the demand on two-week wait referrals.
*http://www.bad.org.uk/shared/get-file.ashx?id=2348&itemtype=document
Impact:
Fellow: Neil Daly
safety, quality and efficiency within hospitals
mental health self-care and education
self-care and education
primary care and urgent care self-care and education
cancer earlier intervention and diagnostics self-care and education
cancer
cardiovascular disease earlier intervention and diagnostics
cancer earlier intervention and diagnostics