And now, an algorithm can predict not only whether they carry a genetic mutation, but which genes were mutated. The study, published Monday in Nature Medicine, is the latest from a Boston-based company called FDNA, one of a few organizations creating software that can help physicians diagnose genetic syndromes based just on a face -- and may serve an important validation of the company's technology, said Yaron Gurovich, the company's chief technology officer. "We went for this high-impact journal to prove beyond any doubt that this technology is good, it performs as we say, we can stand behind it, and now it opens a lot of doors to publish more," he said. The study itself is a collection of experiments testing how the results of algorithms -- FDNA refers to them as DeepGestalt -- stack up against clinicians' diagnoses. In one of the experiments, DeepGestalt's performance was better than random chance when picking which of five genetic mutations might be causing a condition called Noonan syndrome.

Facial recognition can help unlock your phone. Could it also be able to play a far more valuable role in people's lives by identifying whether or not a person has a rare genetic disorder, based exclusively on their facial features? DeepGestalt, an artificial intelligence built by the Boston-based tech company FDNA, suggests that the answer is a resounding "yes." The algorithm is already being used by leading geneticists at more than 2,000 sites in upward of 130 countries around the world. In a new study, published in the journal Nature Medicine, researchers show how the algorithm was able to outperform clinicians when it came to identifying diseases.

The photograph is cropped close on the face of four-year-old Yael, who is smiling and looking as healthy as can be. But a computer analysis of her features says something's not right. She has MR XL Bain Type, the computer predicts--a very rare syndrome that causes a wide range of health problems. It turned out that the computer was right. Yael is one of thousands of children who have contributed to the development of an artificial intelligence system called DeepGestalt that can identify rare genetic disorders based on facial features alone.

People with genetic syndromes sometimes have telltale facial features, but using them to make a quick and cheap diagnosis can be tricky given there are hundreds of possible conditions they may have. A new neural network that analyses photographs of faces can help doctors narrow down the possibilities. Yaron Gurovich at biotechnology firm FDNA in Boston and his team built a neural network to look at the gestalt – or overall impression – of faces and return a list of the 10 genetic syndromes a person is most likely to have. They trained the neural network, called DeepGestalt, on 17,000 images correctly labelled to correspond to more than 200 genetic syndromes. The team then asked the AI to identify potential genetic disorders from a further 502 photographs of people with such conditions.

Researchers are improving the ability of algorithms to help spot the physical characteristics of conditions such as Cornelia de Lange syndrome.Credit: Michael Ares/The Palm Beach Post via ZUMA A deep-learning algorithm is helping doctors and researchers to pinpoint a range of rare genetic disorders by analysing pictures of people's faces. In a paper1 published on 7 January in Nature Medicine, researchers describe the technology behind the diagnostic aid, a smartphone app called Face2Gene. It relies on machine-learning algorithms and brain-like neural networks to classify distinctive facial features in photos of people with congenital and neurodevelopmental disorders. Using the patterns that it infers from the pictures, the model homes in on possible diagnoses and provides a list of likely options. Doctors have been using the technology as an aid, even though it's not intended to provide definitive diagnoses.