Premium
Automatic recognition of the XLHED phenotype from facial images
Author(s) -
HadjRabia Smail,
Schneider Holm,
Navarro Elena,
Klein Ophir,
Kirby Neil,
Huttner Kenneth,
Wolf Lior,
Orin Melanie,
Wohlfart Sigrun,
Bodemer Christine,
Grange Dorothy K.
Publication year - 2017
Publication title -
american journal of medical genetics part a
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.064
H-Index - 112
eISSN - 1552-4833
pISSN - 1552-4825
DOI - 10.1002/ajmg.a.38343
Subject(s) - hypohidrotic ectodermal dysplasia , phenotype , ectodermal dysplasia , medicine , dysplasia , biology , pathology , dermatology , gene , genetics
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.