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PhenoScore quantifies phenotypic variation for rare genetic diseases by combining facial analysis with other clinical features using a machine-learning framework

PhenoScore quantifies phenotypic variation for rare genetic diseases by combining facial analysis with other clinical features using a machine-learning framework

Alexander J. M. Dingemans, Max Hinne, Kim M. G. Truijen, Lia Goltstein, Jeroen van Reeuwijk, Nicole de Leeuw, Janneke Schuurs-Hoeijmakers, Rolph Pfundt, Illja J. Diets, Joery den Hoed, Elke de Boer, Jet Coenen-van der Spek, Sandra Jansen, Bregje W. van Bon, Noraly Jonis, Charlotte W. Ockeloen, Anneke T. Vulto-van Silfhout, Tjitske Kleefstra, David A. Koolen, Philippe M. Campeau, Elizabeth E. Palmer, Hilde Van Esch, Gholson J. Lyon, Fowzan S. Alkuraya, Anita Rauch, Ronit Marom, Diana Baralle, Pleuntje J. van der Sluijs, Gijs W. E. Santen, R. Frank Kooy, Marcel A. J. van Gerven, Lisenka E. L. M. Vissers & Bert B. A. de Vries (2023).
PhenoScore quantifies phenotypic variation for rare genetic diseases by combining facial analysis with other clinical features using a machine-learning framework
PMID: 37550531 ,  DOI: 10.1038/s41588-023-01469-wNat Genet. 2023 Aug 7. Epub ahead of print.