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DIAGNOSIS OF AUTISM IN CHILDREN USING DEEP NEURAL NETWORKS
Abstract
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The autism spectrum disorder is a common term for a group of complex brain and neurodevelopment disorder. The EEG medical imaging technique is a perfect tool for the brain signal analysis. In this study, we identify the variations in EEG signals on the auto-regressive features for classifying the normal and autistic features using Artificial Neural Networks. The simulation result shows that the proposed DNN in classifying the autism features achieves a classification rate of 95.23%.

Authors
N V Kousik
Galgotias University, India

Keywords
Autism Disorder, Auto Regressive Features, Electroencephalography, ANN
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Published By :
ICTACT
Published In :
ICTACT Journal on Data Science and Machine Learning
( Volume: 1 , Issue: 2 , Pages: 49-53 )
Date of Publication :
March 2020
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