Some rare diseases present with symptoms that make it hard for even the most skilled of clinicians to pinpoint the cause, especially in non-European populations. One such disease is 22q11.2 deletion syndrome or DiGeorge syndrome. Affecting from 1 in 3,000 to 1 in 6,000 children, DiGeorge results in multiple defects throughout the body, including a characteristic facial appearance.
Using facial analysis technology, researchers compared a group of 156 individuals, from diverse ethnic backgrounds, confirmed to have the DiGeorge Syndrome to a group of people without. Based on a range of 126 individual facial features, the system made a correct diagnosis for all ethnic groups in the study 96% of the time.
Researchers are hoping that with further advancement, this technology could be expanded so that healthcare providers could send images for analysis, and receive a diagnosis in return. So far this facial recognition system has proven to be accurate in diagnosing cases of Down syndrome, however, the team of researchers behind the DiGeorge study hope it will prove effective in the diagnosis of both Noonan syndrome and Williams syndrome.