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Down syndrome, the most common single cause of human birth defects, produces alterations in physical growth and mental retardation; its early detection is crucial. Children with Down syndrome generally have distinctive facial characteristics, which brings an opportunity for the computer-aided diagnosis of Down syndrome using photographs of patients. In this study, we propose a novel strategy based on machine learning techniques to detect Down syndrome automatically. A modified constrained localdoi:10.1109/embc.2013.6610339 pmid:24110526 dblp:conf/embc/ZhaoROZSSL13 fatcat:k7rawzjzx5dr7ftuxn3y24uxgq