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- W4290785299 abstract "Autism spectrum disorder (ASD) is a neurological developmental disorder that results in infirmity in social behaviour and social communication. Autism is identifiable at any stage of life, but symptoms usually appear in the first two years. This chapter deals with ASD at three different levels: child, adolescent, and adult. For this purpose, the authors have used a dataset from the UCI repository submitted by Fadi Fayez Thabtah, which has 20 features. They proposed new supervised machine learning models to predict the possibility of autism disorder at the adult stage through child, adolescent, and adult datasets. The detailed comparative study of various methods developed is supported by performance measures and respective ROC curves." @default.
- W4290785299 created "2022-08-09" @default.
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- W4290785299 date "2022-06-17" @default.
- W4290785299 modified "2023-09-24" @default.
- W4290785299 title "A Machine Learning Approach for Detecting Autism Spectrum Disorder Using Classifier Techniques" @default.
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- W4290785299 doi "https://doi.org/10.4018/978-1-6684-2443-8.ch001" @default.
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