Facial recognition accuracy in photographs of Thai neonates with Down syndrome among physicians and the Face2Gene application.

Abstract

Down syndrome (DS) is typically recognizable in those who present with multiple dysmorphism, especially in regard to facial phenotypes. However, as the presentation of DS in neonates is less obvious, a phenotype-based presumptive diagnosis is more challenging. Recently, an artificial intelligence (AI) application, Face2Gene, was developed to help physicians recognize specific genetic syndromes by using two-dimensional facial photos. As of yet, there has not been any study comparing accuracy among physicians or applications. Our objective was to compare the facial recognition accuracy of DS in Thai neonates, using facial photographs, among physicians and the Face2Gene. Sixty-four Thai neonates at Thammasat University Hospital, with genetic testing and signed parental consent, were divided into a DS group (25) and non-DS group (39). Non-DS was further divided into unaffected (19) and those affected with other syndromes (20). Our results revealed physician accuracy (89%) was higher than the Face2Gene (81%); however, the application was higher in sensitivity (100%) than physicians (86%). While this application can serve as a helpful assistant in facilitating any genetic syndrome such as DS, to aid clinicians in recognizing DS facial features in neonates, it is not a replacement for well-trained doctors.