Autism Spectrum Disorder (ASD) is a fast spreading neurological disorder in kids of age group of 1 to 5 years. ASD is known as by birth disorder yet it is diagnosed and identified at the age of 2 years or later. Diagnosis and prediction process of ASD are tedious procedures. More research is required in this area to reduce the diagnosis time. Early detection of ASD at underneath two years gives better outcomes. Exact expectation of ASD is likewise significant. In recent research works artificial neural networks become familiar for classification, clustering, pattern recognition, detection and prediction. ANN is a part of machine learning and became relatively familiar as statistical models and regression models. ANN improves classification accuracy in detection of ASD. Co-occurrence matrices are used to reduce computation time of ANN. Present paper proposes a methodology for ASD detection with the help of co-occurrence matrices and artificial neural networks.
Volume 12 | Issue 3
Pages: 579-587
DOI: 10.5373/JARDCS/V12I3/20201226