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Digital Phenotyping for Autism Detection by André Matheus de Moura Dzioba is a document available to read on EtoBox.

What is Digital Phenotyping for Autism Detection about?

- The study assessed the accuracy of an autism screening digital application (app) administered during pediatric well-child visits to 475 children aged 17-36 months. - The app displayed stimuli that elicited behavioral signs of autism like facial expressions and head movements, which were quantified using computer vision and machine learning. - An algorithm combining multiple digital phenotypes from the app showed high diagnostic accuracy with an AUC of 0.90, sensitivity of 87.8%, specificity of 80.8%, N

Author

André Matheus de Moura Dzioba

Language

EN