Researchers advise public to be cautious when using skin cancer diagnosis apps

Source: Xinhua| 2018-07-05 23:22:43|Editor: yan
Video PlayerClose

LONDON, July 5 (Xinhua) -- A lack of testing of some smartphone apps for the diagnosis of skin cancer may risk public safety, according to a study released on Thursday by the University of Birmingham.

The study led by the university, has been outlined at the British Association of Dermatologists'Annual Meeting in Edinburgh. It explores the skin cancer apps on the market, ascertaining how accurate they are, and what the benefits and limitations of these technological solutions are.

Examples of apps include tele-dermatology, which involves sending an image directly to a dermatologist, photo storage, which can be used by individuals to compare photos monthly to look for changes in a mole, and risk calculation, which is based on colour and pattern recognition, or on fractal analysis.

The study found that some of these apps have a comparatively high success rate for the diagnosis of skin cancer. For example, Teledermatology correctly identified 88 percent of people with skin cancer and 97 percent of those with benign lesions.

The team admitted that these types of technology have huge potential, as early diagnosis can make a huge difference when it comes to five-year survival.

But there still are three major failings with some of the apps: a lack of rigorous published trials to show they work and are safe; a lack of input during the app development from specialists to identify which lesions are suspicious; and flaws in the technology used, namely how the photos are analyzed, according to the study.

Future technology will play a huge part in skin cancer diagnosis, but "until adequate validation and regulation of apps is achieved, members of the public should be cautious when using such apps as they come with risk," said Maria Charalambides, of the University of Birmingham's College of Medical and Dental Sciences, who conducted the review.

TOP STORIES
EDITOR’S CHOICE
MOST VIEWED
EXPLORE XINHUANET
010020070750000000000000011105521373042801