Every year, around half a million children worldwide are born with a rare hereditary disease. Obtaining a definitive diagnosis can be difficult and time consuming. In a study of 679 patients with 105 different rare diseases, scientists from the University of Bonn and the Charité - Universitätsmedizin Berlin have shown that artificial intelligence can be used to diagnose rare diseases more efficiently and reliably. A neural network automatically combines portrait photos with genetic and patient data. The results are now presented in the journal "Genetics in Medicine".
Many patients with rare diseases go through lengthy trials and tribulations until they are correctly diagnosed. "This results in a loss of valuable time that is actually needed for early therapy in order to avert progressive damage," explains Prof. Dr. med. Dipl. Phys. Peter Krawitz from the Institute for Genomic Statistics and Bioinformatics at the University Hospital Bonn (UKB). Together with an international team of researchers, he demonstrates how artificial intelligence can be used to make comparatively quick and reliable diagnoses in facial analysis.
The researchers used data of 679 patients with 105 different diseases caused by the change in a single gene. These include, for example, mucopolysaccharidosis (MPS), which leads to bone deformation, learning difficulties and stunted growth. Mabry syndrome also results in intellectual disability. All these diseases have in common that the facial features of those affected show abnormalities. This is particularly characteristic, for example, of Kabuki syndrome, which is reminiscent of the make-up of a traditional Japanese form of theatre. The eyebrows are arched, the eye-distance is wide and the spaces between the eyelids are long.
Read more at University of Bonn
Image: The neural network combines data from portrait images with gene and patient data. (Credit: © Foto: Tori Pantel)