Facial recognition system helps find rare genetic disease

Washington: Scientists have successfully used facial recognition software to diagnose a rare, genetic disease that causes multiple defects like cleft palate and learning problems, but is often hard to pinpoint.

The disease, 22q11.2 deletion syndrome, also known as DiGeorge syndrome and velocardiofacial syndrome, affects about one in 6,000 children.

Since the disease results in multiple defects throughout the body, including cleft palate, heart defects, a characteristic facial appearance and learning problems, healthcare providers often can not pinpoint the disease, especially in diverse populations.

The goal of the study is to help healthcare providers better recognise and diagnose DiGeorge syndrome, deliver critical, early interventions and provide better medical care.

“Human malformation syndromes appear different in different parts of the world,” said Paul Kruszka, a medical geneticist at the US National Human Genome Research Institute (NHGRI).

“Even experienced clinicians have difficulty diagnosing genetic syndromes in non-European populations,” said Kruszka.

The researchers studied the clinical information of 106 participants and photographs of 101 participants with the disease from 11 countries in Africa, Asia and Latin America.

The appearance of someone with the disease varied widely across the groups.

Using facial analysis technology, the researchers compared a group of 156 Caucasians, Africans, Asians and Latin Americans with the disease to people without the disease.

Based on 126 individual facial features, researchers made correct diagnoses 96.6 per cent of the time.