A Review on Deep Learning Algorithms in the Detection of Autism Spectrum Disorder

Title

A Review on Deep Learning Algorithms in the Detection of Autism Spectrum Disorder

Creator

Lamani M.R.; Julian Benadit P.

Description

Autism spectrum disorder (ASD) is a neurodisorder that has an impact on how people interact and communicate with each other for the rest of their lives. Most autistic symptoms appear throughout the first two years of a child's life. This is why autism is called a behavioral disease. If you have a child with ASD, the problem starts in childhood and keeps going through adolescence and adulthood. Deep learning techniques are becoming more common in research on medical diagnosis. In this paper, there is an effort to see if convolutional neural network (CNN), recurrent neural network (RNN), long short-term memory network (LSTM), and a fusion technique known as convolutional recurrent neural network (CRNN) can be used to detect ASD problems in a child, adolescents, and adults. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

Source

Lecture Notes in Networks and Systems, Vol-865, pp. 283-297.

Date

2024-01-01

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

ASD; CNN; CRNN algorithms; Deep learning; LSTM; RNN

Coverage

Lamani M.R., CHRIST (Deemed to Be University), Kanmanike, Kumbalgudu, Mysor Road, Karnataka, Bangalore, 560074, India; Julian Benadit P., CHRIST (Deemed to Be University), Kanmanike, Kumbalgudu, Mysor Road, Karnataka, Bangalore, 560074, India

Rights

Restricted Access

Relation

ISSN: 23673370; ISBN: 978-981999042-9

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-981-99-9043-6_24

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190363447&doi=10.1007%2f978-981-99-9043-6_24&partnerID=40&md5=c4f96946849d73c9d061c1e5f736be60