Toward Machine Learning-Based Psychological Assessment of Autism Spectrum Disorders in School and Community

Sabbir Ahmed; Md Farhad Hossain; Silvia Binte Nur; M. Shamim Kaiser; Mufti Mahmud

doi:10.1007/978-981-16-8826-3_13

Toward Machine Learning-Based Psychological Assessment of Autism Spectrum Disorders in School and Community

Sabbir Ahmed^*
, Md Farhad Hossain
, Silvia Binte Nur
, M. Shamim Kaiser
, Mufti Mahmud

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

45 Scopus citations

Abstract

The sensory processing system of the human body is capable of collecting, developing, and integrating information through sensory organs. Sensory impairment has been discovered in children with autism spectrum disorder (ASD). People with ASD are susceptible to hyper/hypo-sensitivity that might cause changes in information management, affect cognitive impairment, and social reactions to everyday events. This article proposed a questionnaire based on ASD symptoms found in previous studies with 82 questions. Following that, a dataset is created by conducting a survey using the questionnaire. Several machine learning models that can identify ASD and its types are also compared. Among the machine learning models, the artificial neural network achieved an accuracy of 89.8%. Implicit measurements and ecologically sound settings have shown excellent precision in predicting outcomes and the correct classification of populations into categories.

Original language	English
Title of host publication	Proceedings of Trends in Electronics and Health Informatics, TEHI 2021
Editors	M. Shamim Kaiser, Anirban Bandyopadhyay, Kanad Ray, Raghvendra Singh, Vishal Nagar
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	139-149
Number of pages	11
ISBN (Print)	9789811688256
DOIs	https://doi.org/10.1007/978-981-16-8826-3_13
State	Published - 2022
Externally published	Yes
Event	1st International Conference on Trends in Electronics and Health Informatics, TEHI 2021 - Virtual, Online Duration: 16 Dec 2021 → 17 Dec 2021

Publication series

Name	Lecture Notes in Networks and Systems
Volume	376
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	1st International Conference on Trends in Electronics and Health Informatics, TEHI 2021
City	Virtual, Online
Period	16/12/21 → 17/12/21

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Keywords

Artificial neural network (ANN)
Autism spectrum disorder (ASD)
Questionnaire
Random forest (RF)
Support vector machine (SVM)
k-nearest neighbors (KNN)

ASJC Scopus subject areas

Control and Systems Engineering
Signal Processing
Computer Networks and Communications

Access to Document

10.1007/978-981-16-8826-3_13

Cite this

Ahmed, S., Hossain, M. F., Nur, S. B., Shamim Kaiser, M., & Mahmud, M. (2022). Toward Machine Learning-Based Psychological Assessment of Autism Spectrum Disorders in School and Community. In M. S. Kaiser, A. Bandyopadhyay, K. Ray, R. Singh, & V. Nagar (Eds.), Proceedings of Trends in Electronics and Health Informatics, TEHI 2021 (pp. 139-149). (Lecture Notes in Networks and Systems; Vol. 376). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-16-8826-3_13

Ahmed, Sabbir ; Hossain, Md Farhad ; Nur, Silvia Binte et al. / Toward Machine Learning-Based Psychological Assessment of Autism Spectrum Disorders in School and Community. Proceedings of Trends in Electronics and Health Informatics, TEHI 2021. editor / M. Shamim Kaiser ; Anirban Bandyopadhyay ; Kanad Ray ; Raghvendra Singh ; Vishal Nagar. Springer Science and Business Media Deutschland GmbH, 2022. pp. 139-149 (Lecture Notes in Networks and Systems).

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abstract = "The sensory processing system of the human body is capable of collecting, developing, and integrating information through sensory organs. Sensory impairment has been discovered in children with autism spectrum disorder (ASD). People with ASD are susceptible to hyper/hypo-sensitivity that might cause changes in information management, affect cognitive impairment, and social reactions to everyday events. This article proposed a questionnaire based on ASD symptoms found in previous studies with 82 questions. Following that, a dataset is created by conducting a survey using the questionnaire. Several machine learning models that can identify ASD and its types are also compared. Among the machine learning models, the artificial neural network achieved an accuracy of 89.8\%. Implicit measurements and ecologically sound settings have shown excellent precision in predicting outcomes and the correct classification of populations into categories.",

keywords = "Artificial neural network (ANN), Autism spectrum disorder (ASD), Questionnaire, Random forest (RF), Support vector machine (SVM), k-nearest neighbors (KNN)",

author = "Sabbir Ahmed and Hossain, \{Md Farhad\} and Nur, \{Silvia Binte\} and \{Shamim Kaiser\}, M. and Mufti Mahmud",

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Ahmed, S, Hossain, MF, Nur, SB, Shamim Kaiser, M & Mahmud, M 2022, Toward Machine Learning-Based Psychological Assessment of Autism Spectrum Disorders in School and Community. in MS Kaiser, A Bandyopadhyay, K Ray, R Singh & V Nagar (eds), Proceedings of Trends in Electronics and Health Informatics, TEHI 2021. Lecture Notes in Networks and Systems, vol. 376, Springer Science and Business Media Deutschland GmbH, pp. 139-149, 1st International Conference on Trends in Electronics and Health Informatics, TEHI 2021, Virtual, Online, 16/12/21. https://doi.org/10.1007/978-981-16-8826-3_13

Toward Machine Learning-Based Psychological Assessment of Autism Spectrum Disorders in School and Community. / Ahmed, Sabbir; Hossain, Md Farhad; Nur, Silvia Binte et al.
Proceedings of Trends in Electronics and Health Informatics, TEHI 2021. ed. / M. Shamim Kaiser; Anirban Bandyopadhyay; Kanad Ray; Raghvendra Singh; Vishal Nagar. Springer Science and Business Media Deutschland GmbH, 2022. p. 139-149 (Lecture Notes in Networks and Systems; Vol. 376).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Mahmud, Mufti

PY - 2022

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Ahmed S, Hossain MF, Nur SB, Shamim Kaiser M, Mahmud M. Toward Machine Learning-Based Psychological Assessment of Autism Spectrum Disorders in School and Community. In Kaiser MS, Bandyopadhyay A, Ray K, Singh R, Nagar V, editors, Proceedings of Trends in Electronics and Health Informatics, TEHI 2021. Springer Science and Business Media Deutschland GmbH. 2022. p. 139-149. (Lecture Notes in Networks and Systems). doi: 10.1007/978-981-16-8826-3_13