Scientists have developed an artificial intelligence (AI) system that uses portrait photographs (facial analysis), in combination with genetic and patient data, to effectively diagnose rare diseases.
About half a million children are born with hereditary diseases annually, and often, obtaining definitive diagnoses can be time consuming. The sooner patients have access to treatment and therapy, the greater chance of averting progressive damage, hence the urgency for speedy diagnoses.
Researchers have now shown how artificial intelligence can be used to make comparatively quick and reliable diagnoses in facial analysis. The Neural Network automatically combines portrait photos with genetic and patient data – the combination of which is proving to be effective in diagnosing rare conditions.
They used data of 679 patients, with 105 different diseases caused by the change in a single gene. These include, for example, mucopolysaccharidosis (MPS), (which leads to bone deformation, learning difficulties and stunted growth) and Mabry syndrome, which also results in intellectual disability. All these diseases have in common, is the fact that the facial features of those affected show abnormalities.
Kabuki syndrome, for example, has distinct features (the eyebrows are arched, the eye-distance is wide and the spaces between the eyelids are long) which can automatically be detected. Together with the clinical symptoms of the patients and genetic data, it is possible to calculate with high accuracy which disease is most likely to be involved simply from a photograph.
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