Article
PhenoScore quantifies phenotypic variation for rare genetic diseases by combining facial analysis with other clinical features using a machine-learning framework.
Nature genetics - 1 Sept 2023
Dingemans Alexander J M, Hinne Max, Truijen Kim M G, Goltstein Lia, van Reeuwijk Jeroen, de Leeuw Nicole, Schuurs-Hoeijmakers Janneke, Pfundt Rolph, Diets Illja J, den Hoed Joery, de Boer Elke, Coenen-van der Spek Jet, Jansen Sandra, van Bon Bregje W, Jonis Noraly, Ockeloen Charlotte W, Vulto-van Silfhout Anneke T, Kleefstra Tjitske, Koolen David A, Campeau Philippe M, Palmer Elizabeth E, Van Esch Hilde, Lyon Gholson J, Alkuraya Fowzan S, Rauch Anita, Marom Ronit, Baralle Diana, van der Sluijs Pleuntje J, Santen Gijs W E, Kooy R Frank, van Gerven Marcel A J, Vissers Lisenka E L M, de Vries Bert B A
Abstract excerpt
Several molecular and phenotypic algorithms exist that establish genotype-phenotype correlations, including facial recognition tools. However, no unified framework that investigates both facial data and other phenotypic data directly from individuals exists. We developed PhenoScore: an open-source, artificial intelligence-based phenomics framework, combining facial recognition technology with Human Phenotype...
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