Facial Analysis Technology Aids Diagnoses Of Genetic Disorders

Facial analysis technology that is becoming easier to use and more accessible may help geneticists narrow down possible genetic diagnoses behind disorders that often involve dysmorphic facial features. Researchers at the University of Oxford in the United Kingdom have developed a computer application based on an algorithm that employs facial analysis technology to extract various phenotypic information about facial dysmorphisms from nonclinical photographs. The application uses machine learning, a type of artificial intelligence that learns from data instead of following explicit programmed instructions. It then builds a description of the face structure, known as the facial mesh, and compares it against data from other facial meshes in the system before delivering a list of possible genetic diagnoses. The algorithm becomes better at spotting facial phenotypes associated with a disorder as it analyzes more photos of faces with those specific features [Ferry et al., 2014]. In contrast to older facial analysis systems that rely on costly equipment to analyze three-dimensional (3-D) images, the Oxford-based researchers used easily accessible two-dimensional (2-D) photographs of children’s faces to analyze specific facial features that are associated with up to 40% of genetic disorders.