Advances in computer-assisted syndrome recognition and differentiation in a set of metabolic disorders

Abstract
Significant improvements in automated image analysis have been achieved over the recent years and tools are now increasingly being used in computer-assisted syndromology. However, the recognizability of the facial gestalt might depend on the syndrome and may also be confounded by severity of phenotype, size of available training sets, ethnicity, age, and sex. Therefore, benchmarking and comparing the performance of deep-learned classification...
Paper Details
Title
Advances in computer-assisted syndrome recognition and differentiation in a set of metabolic disorders
Published Date
Nov 14, 2017
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