Development and evaluation of a machine learning-based point-of-care screening tool for genetic syndromes in children: a multinational retrospective study
Development and evaluation of a machine learning-based point-of-care screening tool for genetic syndromes in children: a multinational retrospective study
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DOI：
10.1016/s2589-7500(21)00137-0
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发表时间：
2021-09-20
影响因子：
30.8
通讯作者：
Linguraru, Marius George
中科院分区：
文献类型：
--
作者：
Porras, Antonio R.;Rosenbaum, Kenneth;Linguraru, Marius George
遗传综合征的诊断延迟是常见的，特别是在低收入和中等收入国家，遗传筛查服务有限。因此，我们的目标是开发和评估一种基于机器学习的筛查技术，该技术使用面部照片来评估儿童出现遗传综合征的风险，以便在护理点使用。方法在这项回顾性研究中，我们开发了一种基于深度神经网络和面部统计形状模型的面部深度表型技术，用于筛查儿童遗传综合征。我们在儿童（年龄）的面部照片上训练了机器学习模型
Background Delays in the diagnosis of genetic syndromes are common, particularly in low and middle-income countries with limited access to genetic screening services. We, therefore, aimed to develop and evaluate a machine learning-based screening technology using facial photographs to evaluate a child's risk of presenting with a genetic syndrome for use at the point of care. Methods In this retrospective study, we developed a facial deep phenotyping technology based on deep neural networks and facial statistical shape models to screen children for genetic syndromes. We trained the machine learning models on facial photographs from children (aged