1133 GMT December 04, 2020
Research suggested that it is possible for a computer algorithm to detect coronary artery disease by analyzing four photographs of a person’s face, according to dailymail.co.uk.
More than 6,800 people took part in the research, providing nurses with selfie photos which were then analyzed with artificial intelligence.
The computer was trained to spot certain facial features which are associated with an increased risk of heart disease, but are difficult for doctors to spot.
These include thinning or grey hair, wrinkles, age spots, ear lobe crease and xanthelasma, which are small, yellow deposits of cholesterol underneath the skin.
The computer analysis was found to correctly predict 80 percent of cases — making it just as accurate as standard tests.
Heart and circulatory diseases cause more than a quarter of all deaths in the UK, nearly 170,000 deaths each year.
The research was led by Professor Zhe Zheng, from China’s National Center for Cardiovascular Diseases, who said the selfie screening tool could be a ‘cheap, simple and effective’ way of identifying patients who need further treatment or tests.
“It is a step towards the development of a deep learning-based tool that could be used to assess the risk of heart disease, either in outpatient clinics or by means of patients taking ‘selfies’ to perform their own screening,” he explained.
“Our ultimate goal is to develop a self-reported application for high risk communities to assess heart disease risk in advance of visiting a clinic.
“However, the algorithm requires further refinement and external validation in other populations and ethnicities.”
Co-researcher Professor Xiang-Yang Ji, added: “The algorithm had a moderate performance, and additional clinical information did not improve its performance, which means it could be used easily to predict potential heart disease based on facial photos alone.
“The cheek, forehead and nose contributed more information to the algorithm than other facial areas.
“However, we need to improve the specificity as a false positive rate of as much as 46 percent may cause anxiety and inconvenience to patients, as well as potentially overloading clinics with patients requiring unnecessary tests.”
The paper was published in the European Heart Journal.