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Am J Med Genet A. 2017 Sep;173(9):2408-2414. doi: 10.1002/ajmg.a.38343. Epub 2017 Jul 10.

Automatic recognition of the XLHED phenotype from facial images.

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Department of Dermatology, Reference center for genodermatoses and rare skin diseases (MAGEC), INSERM U1163, Université Paris Descartes-Sorbonne Paris Cité, Institut Imagine, Hôpital Universitaire Necker-Enfants Malades, Paris, France.
Competence Center for Ectodermal Dysplasias, Department of Pediatrics, University Hospital Erlangen, Erlangen, Germany.
Center for Biomedical Network Research on Rare Diseases (CIBERER), C/Alvaro de Bazan, 10 Bajo Valencia, Spain.
Departments of Orofacial Sciences and Pediatrics, Program in Craniofacial Biology, and Institute for Human Genetics, University of California San Francisco, San Francisco, California.
Edimer Pharmaceuticals Inc, Cambridge Pkwy, Cambridge, Massachusetts.
Novartis/NIBR/NIDU, Cambridge, Massachusetts.
FDNA Inc, Boston, Massachusetts.
Department of Computer Sciences, University of Tel Aviv, Ramat-Aviv, Tel Aviv-Jaffa, Israel.
Department of Pediatrics, Washington University School of Medicine, St. Louis, Missouri.


X-linked hypohidrotic ectodermal dysplasia (XLHED) is a genetic disorder that affects ectodermal structures and presents with a characteristic facial appearance. The ability of automated facial recognition technology to detect the phenotype from images was assessed . In Phase 1 of this study we examined if the age of male patients affected the technology's recognition. In Phase 2 we investigated how well the technology discriminated affected males cases from female carriers and from individuals with other ectodermal dysplasia syndromes. The system detected XLHED to be the most likely diagnosis in all genetically confirmed affected male patients of all ages, and in 55% of heterozygous females. Interestingly, patients with other ED syndromes were also detected by the XLHED-targeted analysis, consistent with shared developmental features. Thus the automated facial recognition system represents a promising non-invasive technology to screen patients at all ages for a possible diagnosis of ectodermal dysplasia, with greatest sensitivity and specificity for males affected with XLHED.


anhidrotic/hypohidrotic ectodermal dysplasia; automated facial recognition; dermatology; dysmorphology; pediatrics

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