Facial Recognition Software Helps Diagnose Rare Genetic Disease
Researchers have used facial recognition software to diagnose a rare, genetic disease in Africans, Asians and Latin Americans. The disease is known as DiGeorge syndrome and velocardiofacial syndrome, affects 1 in 3,000 to 1 in 6,000 children.
The study was successful because the disease defects throughout the multiple parts of the body, including cleft palate, heart defects, a characteristic facial appearance and learning problems, healthcare providers often can’t pinpoint the disease, especially in diverse populations.
The research was carried out by scientists with the National Human Genome Research Institute, as part of the National Institutes of Health, along with their collaborators, and was published March 23 in the American Journal of Medical Genetics.
The goal of the study is to help healthcare providers better recognize and diagnose DiGeorge syndrome, deliver critical, early interventions and provide better medical care.
Using facial recognition 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 for all ethnic groups 96.6 percent of the time.
Researchers hope to further develop the facial recognition technology – similar to that used in airports and on Facebook – so that healthcare providers can one day take a cell phone picture of their patient, have it analyzed and receive a diagnosis.
This technology was also very accurate in diagnosing Down syndrome, according to a study published in December 2016. The same team of researchers will next study Noonan syndrome and Williams syndrome, both of which are rare but seen by many clinicians.
The Atlas Of Human Malformations In Diverse Populations
DiGeorge syndrome and Down syndrome are both included in the Atlas of Human Malformations in Diverse Populations, a program launched in 2016. Upon its completion, this atlas will represent a comprehensive and exhaustive database of distinct inherited diseases worldwide.
Additionally, the photos of these conditions will be accompanied by short descriptions of affected people. These descriptions would allow clinicians to search diseases based on a series of categories, from continental region to the phenotype or the syndrome.