Year: 2025
Type: article
Abstract: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that affects communication, behavior, and social interaction. Early diagnosis plays a critical role in improving the quality of life of individuals affected by ASD. This study explores the application of machine learning algorithms to effectively analyze and detect autism spectrum disorder. By utilizing a publicly available dataset and applying algorithms such as Support Vector Machine (SVM), Random Forest, and Decision Tree, the model aims to achieve high accuracy in prediction. The results demonstrate that machine learning can be a valuable tool in assisting healthcare professionals in the early and efficient detection of ASD.
Authors: KAVYA K, S Manjunatha -
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: hybrid
OpenAlex ID: W4414379209
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