A Deep Neural Network-Based Model for Screening Autism Spectrum Disorder Using the Quantitative Checklist for Autism in Toddlers (QCHAT)

Autor/inn/en	Mujeeb Rahman, K. K.; Monica Subashini, M.
Titel	A Deep Neural Network-Based Model for Screening Autism Spectrum Disorder Using the Quantitative Checklist for Autism in Toddlers (QCHAT)
Quelle	In: Journal of Autism and Developmental Disorders, 52 (2022) 6, S.2732-2746 (15 Seiten) PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Mujeeb Rahman, K. K.) ORCID (Monica Subashini, M.)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0162-3257
DOI	10.1007/s10803-021-05141-2
Schlagwörter	Screening Tests; Autism; Pervasive Developmental Disorders; Artificial Intelligence; Clinical Diagnosis; Toddlers; Mathematics; Evaluation Methods; Autism Diagnostic Observation Schedule; Childhood Autism Rating Scale + Suchen Sie Ihr Suchwort? Screening-Verfahren; Autismus; Künstliche Intelligenz; Infant; Infants; Toddler; Kleinkind; Mathematik
Abstract	Autism spectrum disorder (ASD) is an abnormal condition of brain development characterized by impaired cognitive ability, speech and human interactions, in addition to a set of repetitive and stereotyped patterns of behaviours. Although no cure for autism exists, early medical intervention can improve the associated symptoms and quality of life. Several manually executed screening tools help to identify the ASD-related behavioural traits in the children that assists the specialist in diagnosing the disease accurately. The quantitative checklist for autism in toddlers (QCHAT) is one of the efficient screening tools used worldwide for ASD screening. ASD diagnosis requires many different manually administered procedures; hence long delay is encountered in getting final results. In recent years, deep neural network (DNN) popularity has been immensely increasing due to its supremacy in solving complex problems. The objective of this research is to apply algorithms, based on the deep neural network (DNN) to identify patients with ASD from the QCHAT datasets. We have used two datasets, the QCHAT and QCHAT-10, in our study. The results obtained show that related to contemporary techniques, the proposed method brings better performance. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01