SELFIES could be used to screen for signs of heart disease

SELFIES could be used to screen for signs of heart disease by analysing photos of a person’s face, new research suggests

  • Selfies could be an cheap and effective way to screen for signs of heart disease
  • A computer was trained to spot facial features associated with increased risk
  • It correctly predicted 80 per cent of cases – as accurate as standard test

Selfies could be an cheap and effective way to screen for signs of heart disease, a study has found.

Research suggests that it is possible for a computer algorithm to detect coronary artery disease by analysing four photographs of a person’s face.

More than 6,800 people took part in the research, providing nurses with selfie photos which were then analysed 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.

Research suggests that it is possible for a computer algorithm to detect coronary artery disease by analysing four photographs of a person’s face

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 per cent 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 Centre 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% 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.

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