Facial recognition successfully used to diagnose rare genetic diseases

Researchers have successfully used facial recognition technology to detect a rare genetic disease called DiGeorge syndrome in patients. This breakthrough could prove to be a new diagnostic tool for doctors who often have trouble diagnosing the disease due to its many symptoms. The condition is estimated to affect one in 3000 to 6000 kids, and causes defects like heart problems and cleft palate.

The work was accomplished by the NIH's National Human Genome Research Institute, where researchers used facial recognition technology to detect the facial features indicative of this disease. A total of 126 facial features were identified and can be used to diagnose DiGeorge syndrome with a 96.6% accuracy across all ethnic groups.

Speaking about this, medical geneticist Paul Kruszka said:

Human malformation syndromes appear different in different parts of the world. Even experienced clinicians have difficulty diagnosing genetic syndromes in non-European populations.

That's why researchers used 156 volunteers spanning Caucasian, African, Asian, and Latin American ethnicities to identify the many different facial features common to the disease. Even better, the technology is not limited to only this condition, but has already been proven capable of diagnosing Down syndrome; researchers are looking into the possibility of also using it to diagnose Williams and Noonan syndromes.

SOURCE: EurekAlert