Detection of Autism Spectrum Disorder Using Machine Learning
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Date
2024
Journal Title
Journal ISSN
Volume Title
Publisher
NHCE
Abstract
The exponential disorder known as autism spectrum disease has a profound impact on how individuals behave and engage in their communities. Children diagnosed with autism spectrum disorder may find it difficult to interact socially and learn new words. Unusual behavior that parents observe in their autistic children includes poor motor skills and repetitive movements of their hands and head, as well as violent head and body jerks. While there is no known cure for ASD, many children's lives can be greatly enhanced by early intervention. For this reason, ASD is called a lifelong illness. Depending on the illness's complexity, severity, and symptoms, multiple factors can contribute to ASD. Environment and genetics play important roles. Early autism prediction has become effortless because of artificial intelligence and machine learning (ML). Even though several studies have been carried out utilizing diverse methodologies, these inquiries have not produced any definitive results regarding the capacity to anticipate autism characteristics across different age groups. Although the model can be applied to both toddlers and adults, the primary focus of this project is the early detection of autism disorder in toddlers. ASD symptoms typically appear between the ages of 12 and 18 months, so when they are identified early on, a toddler's communication skills can be improved through therapy.