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1Laboratory of Protein Phosphorylation and Proteomics, KU Leuven Department of Cellular and Molecular Medicine, University of Leuven, Leuven, Belgium 2KU Leuven Institute for Rare Diseases (Leuven.IRD), Leuven, Belgium 3Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway 4Department of Clinical Science, University of Bergen, Bergen, Norway 5Institute for Genomic Statistics and Bioinformatics, University Hospital Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn,...
The authors have declared no competing interest. This study did not receive any funding. I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.
Abstract Many monogenic disorders cause a characteristic facial morphology. Artificial intelligence can support physicians in recognizing these patterns by associating facial phenotypes with the underlying syndrome through training on thousands of patient photographs. However, this ‘supervised’ approach means that diagnoses are only possible if the disorder was part of the training set.
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