Could software reveal whether Abraham Lincoln had Marfan syndrome? (Image: Alexander Gardner/Hulton Archive/Getty)

Doctors faced with the tricky task of spotting rare genetic diseases in children may soon be asking parents to email their family photos. A computer program can now learn to identify rare conditions by analysing a face from an ordinary digital photograph. It should even be able to identify unknown genetic disorders if groups of photos in its database share specific facial features.

Rare genetic disorders are thought to affect 6 per cent of people. Genetic tests exist for the more common conditions such as Down’s syndrome, but many people with the rarer disorders never get a proper clinical diagnosis. Genetic tests aren’t available for many conditions because the gene variants that cause them haven’t been identified. This means doctors often have to rely on the pronounced facial features that occur in between 30 and 40 per cent of rare disorders to make a diagnosis, but few people are trained to recognise them.

“Clinicians skilled in the use of facial features to support diagnosis are few and far between,” says Alastair Kent, director of the charity Genetic Alliance UK. “As a result, families frequently experience long delays – years rather than months – before they receive a diagnosis for their child.”


The software developed by Christoffer Nellåker and Andrew Zisserman of the University of Oxford and their colleagues should help family doctors or general paediatricians make a preliminary diagnosis. “The idea is to offer it to health systems right across the world because all you need is a computer and a digital photo,” says Nellåker.

Diagnosing Abe

To train the system, Nellåker’s team fed a computer vision algorithm 1363 publicly available pictures of people with eight genetic disorders, including Down’s syndrome, fragile X syndrome and progeria (fourth, fifth and sixth in the graphic below). The computer learned to identify each condition from a pattern of 36 facial features in each shot, such as the shapes of eyes, brows, lips and noses.

Each of the disorders used to train the software affects a face differently (See the full-size image) (Image: University of Oxford)

“It automatically analyses the picture and annotates key feature points, producing from that a description of the face which expands the features that are important for distinctiveness,” Nellåker says. These features are then compared with those from pictures of patients with confirmed disorders, allowing the system to suggest and rank predictions for new patients.

To show that it works, the team analysed photos of people with known genetic disorders. The accuracy of the software increases with the number of photos of a specific disorder it learns from. For the eight training diseases, for example, each disorder was represented by between 100 and 283 images. On average, this resulted in 93 per cent of the predictions being correct.

The team have since expanded the software so that it recognises 90 disorders. It can’t give an exact diagnosis yet, but based on the 2754 faces now in the database, the researchers estimate that the system makes it almost 30 times more likely that someone will make a correct diagnosis than by chance alone.

For example, after looking at photos of former US president Abraham Lincoln, the software ranked Marfan syndrome – a disorder resulting in unusually large features, which some believe he had – as the seventh most likely diagnosis out of 91 syndromes.

Elegant and accessible

“It’s not sufficiently accurate to provide a rock-solid diagnosis, but it helps narrow down the possibilities,” says Nellåker. He says that the system could in theory be used to screen for rare genetic diseases in newborns, but sees it mainly being used when parents who are worried about abnormalities in their children go to genetic counsellors.

The biggest benefit is likely to be the ease of access to the system, says David FitzPatrick of the Western General Hospital in Edinburgh, UK, the clinical geneticist who validated all the cases used to train the system. “Worldwide, its main use will be in countries where you don’t have any access to clinical genetics at all.”

Researchers have already built up similar databases of three-dimensional images for computers to diagnose rare diseases but using ordinary photos should make the technique more widely accessible.

“3D images are still hard and relatively expensive to acquire, and people need to visit the hospital for them to be taken,” says Peter Claes of the Catholic University of Leuven (KUL), Belgium, which has an extensive 3D image databank. “Now you can do it from home with your smart phone, which is elegant.”

Charities representing patients with rare diseases have welcomed the new system. “It’s potentially a tremendous step forward in shortening the diagnostic journey that families embark on following birth of a child with dysmorphic features,” says Kent. “If validated, it will provide access to expert advice and guidance for families more quickly and efficiently than is currently possible.”

To make the system even more powerful, Nellåker and his colleagues hope to train the algorithm to analyse faces in profile as well as full frontal pictures. Another goal is to couple the software with programs that analyse DNA for distinctive mutations, so that the facial and genetic features of any new disorder identified can be explored simultaneously.

Journal reference: eLife, DOI: 0.7554/eLife.02020