Proceedings of the Second International Conference on Emerging Trends in Engineering (ICETE 2023)

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Rule Based Classifier for the Detection of Autism in Children

Authors
Kusumalatha Karre1, 2, *, Y. Ramadevi3
1Sreenidhi Institute of Science and Technology, Hyderabad, India
2Osmania University, Hyderabad, India
3Chaitanya Bharathi Institute of Technology, Hyderabad, India
*Corresponding author. Email: kusumalatha.karre@gmail.com
Corresponding Author
Kusumalatha Karre
Available Online 9 November 2023.
DOI
10.2991/978-94-6463-252-1_10How to use a DOI?
Keywords
Autism Diagnosis; classification; machine learning; Rule based model
Abstract

Autism is a developmental disorder that hinders the life of an autistic child with poor communication and a lack of social skills to carry out their day-to-day work. Detecting autism is very important at an early stage to help the child overcome their learning disabilities. Generally, Autism is diagnosed by specialists in hospitals or therapy centers using procedures that are expensive and time-consuming. Research has been carried out to use various machine learning algorithms to develop intelligent classifiers for autism which can improve accuracy and reduce time. In this paper, we propose a Rule based classifier that generates rules that are combined with machine learning algorithms to detect autism in children by using the QCHAT screening tool. It is the first time Rule based machine learning has been used on a QCHAT screening tool that detects autism during 18–30 months of age. The dataset of QCHAT with rule based classifier has been used for detecting autism and achieved an accuracy of 97.37%. This would be helpful for the doctors and parents to diagnose the child with autism and initiate necessary therapies which can help the child to develop to the fullest.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the Second International Conference on Emerging Trends in Engineering (ICETE 2023)
Series
Advances in Engineering Research
Publication Date
9 November 2023
ISBN
10.2991/978-94-6463-252-1_10
ISSN
2352-5401
DOI
10.2991/978-94-6463-252-1_10How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Kusumalatha Karre
AU  - Y. Ramadevi
PY  - 2023
DA  - 2023/11/09
TI  - Rule Based Classifier for the Detection of Autism in Children
BT  - Proceedings of the Second International Conference on Emerging Trends in Engineering (ICETE 2023)
PB  - Atlantis Press
SP  - 79
EP  - 86
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-252-1_10
DO  - 10.2991/978-94-6463-252-1_10
ID  - Karre2023
ER  -