AI App Identifies Rare Genetic Disorders from Photos of Patients’ Faces

Deep-learning algorithms could help doctors narrow in on the causes of certain medical conditions, say researchers.

Written byCatherine Offord

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A group of image-analyzing algorithms designed by Boston-based startup FDNA can diagnose certain genetic diseases based on people’s faces, according to a study published yesterday (January 7) in Nature Medicine. The algorithms, collectively termed DeepGestalt by the company, rely on deep learning and computer vision to identify patterns in facial photos of patients and identify which of multiple possible genetic mutations could be behind a person’s condition.

The approach “is clearly not perfect,” says FDNA’s chief technology officer, Yaron Gurovich. “[But] it’s still much better than humans are at trying to do this.”

DeepGestalt powers the company’s app, Face2Gene, which has been freely available to health care professionals since 2014. Doctors have already started using the technology as an aid, according to Nature, although the tool is not intended to be used to provide a definitive diagnosis.

The current study was designed to demonstrate the technology’s ...

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Meet the Author

Catherine Offord
After undergraduate research with spiders at the University of Oxford and graduate research with ants at Princeton University, Catherine left arthropods and academia to become a science journalist. She has worked in various guises at The Scientist since 2016. As Senior Editor, she wrote articles for the online and print publications, and edited the magazine’s Notebook, Careers, and Bio Business sections. She reports on subjects ranging from cellular and molecular biology to research misconduct and science policy. Find more of her work at her website.
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