Associative classification mining in the behavior study of autism spectrum disorder
Conference proceedings article
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Publication Details
Author list: Sunsirikul S., Achalakul T.
Publisher: Hindawi
Publication year: 2010
Volume number: 3
Start page: 279
End page: 283
Number of pages: 5
ISBN: 9781424455850
ISSN: 0146-9428
eISSN: 1745-4557
Languages: English-Great Britain (EN-GB)
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Abstract
The number of children diagnosed with Autism Spectrum Disorder (ASD) has increased in the past few years and the root cause of the symptom cannot yet be determined. The diagnosis today relies heavily on the observation of children's behaviors. This paper presents a technique to investigate the behavior factor associations, and to classify these relations using classification based on association (CBA). Our experiments used actual patient profiles from two hospitals in Thailand. This dataset was categorized by doctors into two types: Autism and Pervasive Developmental Disorder - Not Otherwise Specified (PDD-NOS). Our analysis results show several interesting behavior patterns in autism disorder. These results provide valuable information for doctors to conduct further studies in the early intervention of autistic symptoms. The goal of our research is to develop a data analysis tool to aid doctors in the diagnosis process in the future. ฉ2010 IEEE.
Keywords
Classification based on association, Medical data analysis
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