Development of a computer-aided tool for the pattern ...
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www.nature.com/scientificreports
OPEN
Received: 27 October 2017 Accepted: 4 June 2018 Published: xx xx xxxx
Development of a computer-aided tool for the pattern recognition of facial features in diagnosing Turner syndrome: comparison of diagnostic accuracy with clinical workers Shi Chen1,2, Zhou-xian Pan3, Hui-juan Zhu1, Qing Wang4,5, Ji-Jiang Yang4, Yi Lei6, Jian-qiang Li7 & Hui Pan1,2,8 Technologies applied for the recognition of facial features in diagnosing certain disorders seem to be promising in reducing the medical burden and improve the efficiency. This pilot study aimed to develop a computer-assisted tool for the pattern recognition of facial features for diagnosing Turner syndrome (TS). Photographs of 54 patients with TS and 158 female controls were collected from July 2016 to May 2017. Finally, photographs of 32 patients with TS and 96 age-matched controls were included in the study that were further divided equally into training and testing groups. The process of automatic classification consisted of image preprocessing, facial feature extraction, feature reduction and fusion, automatic classification, and result presentation. A total of 27 physicians and 21 medical students completed a web-based test including the same photographs used in computer testing. After training, the automatic facial classification system for diagnosing TS achieved a 68.8% sensitivity and 87.5% specificity (and a 67.6% average sensitivity and 87.9% average specificity after resampling), which was significantly higher than the average sensitivity (57.4%, P
