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All Journal International Journal of Electrical and Computer Engineering
Nagashree Nagesh
Nagarjuna College of Engineering and Technology
Computer Science & IT Electrical & Electronics Engineering

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An architectural framework for automatic detection of autism using deep convolution networks and genetic algorithm Nagashree Nagesh; Premjyoti Patil; Shantakumar Patil; Mallikarjun Kokatanur
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i2.pp1768-1775

Abstract

The brainchild in any medical image processing lied in how accurately the diseases are diagnosed. Especially in the case of neural disorders such as autism spectrum disorder (ASD), accurate detection was still a challenge. Several noninvasive neuroimaging techniques provided experts information about the functionality and anatomical structure of the brain. As autism is a neural disorder, magnetic resonance imaging (MRI) of the brain gave a complex structure and functionality. Many machine learning techniques were proposed to improve the classification and detection accuracy of autism in MRI images. Our work focused mainly on developing the architecture of convolution neural networks (CNN) combining the genetic algorithm. Such artificial intelligence (AI) techniques were very much needed for training as they gave better accuracy compared to traditional statistical methods.
Co-Authors Mallikarjun Kokatanur Premjyoti Patil Shantakumar Patil