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AB045. Studying the probabilities of Down syndrome recognition in Thai children using de-identified computer-aided facial features analysis

机译:AB045。使用未识别的计算机辅助面部特征分析研究泰国儿童唐氏综合症的识别可能性

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摘要

BackgroundCraniofacial dysmorphism plays a major part in the evaluation of many genetic syndromes. Facial pattern recognition has been typically used by clinicians before sending the patients’ blood for specific diagnostic tests. However, the number of genetic syndromes is enormous, and the specific facial features are difficult to memorize for all syndromes. Therefore facial dysmorphology novel analysis (FDNA) technology, innovative software, was developed to help clinicians recognize probable genetic syndromes from patients’ facial gestalts by ranking. Ethnic differences might have a major effect on patients’ facial features. The FDNA database mainly consists of Caucasian patients; therefore, the probability recognition for Asian patients may be limited. The aim of this project is to test the software's recognition probability (sensitivity) on Thai Down Syndrome (DS) children compared to Thai non-Down syndrome (non-DS) children (specificity).
机译:背景颅面畸形在许多遗传综合征的评估中起着重要作用。临床医生通常在将患者的血液送往特定的诊断测试之前使用面部模式识别。然而,遗传综合症的数量巨大,并且对于所有综合症都难以记住特定的面部特征。因此,开发了面部畸形学新颖分析(FDNA)技术和创新软件,以帮助临床医生通过排名从患者的面部姿势识别可能的遗传综合征。种族差异可能会对患者的面部特征产生重大影响。 FDNA数据库主要由白人患者组成。因此,对亚洲患者的概率识别可能会受到限制。该项目的目的是测试泰国唐氏综合症(DS)儿童与泰国非唐氏综合症(non-DS)儿童(特异性)相比,该软件的识别概率(敏感性)。

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