In diesem Wintersemester wird die im letzten Jahr erfolgreich gestartete Vortragsreihe Medical Information Sciences fortgesetzt. Renommierte Wissenschaftlerinnen und Wissenschaftler unterschiedlicher Fachdisziplinen und Forschungsstandorte geben jeden Dienstag ab 17:30 Uhr Einblicke in aktuelle Fragestellungen und Anwendungsgebiete des breiten Forschungsfeldes Medical Information Sciences.

Deep convolutional neural networks (DCNNs) can be trained to recognize and classify rare genetic disorders based on their characteristic facial features. GestaltMatcher is such an AI that learned to construct a clinical face phenotype space (CFPS) in which portrait images can be placed. Distances in between medical images in the CFPS can be used to quantify syndromic similarities. Cluster analysis in that space reveals close proximity of molecular pathway diseases and can, therefore, be used to support "lumping decisions". Furthermore, the pleiotropic genes causing multiple disorders can also result in distinct facial gestalt. Thus, cluster analysis can also provide evidence for "splitting decisions", that is indication for different pathomechanisms based on gestalt analysis.