Classification by Feature Selection of Autism Spectrum Disorder with Automatic Programming Methods

Autism Spectrum Disorder (Autism Spectrum Disorder, OSB) is a neuro-developmental disorder that negatively affects the communication of individuals due to the cells in the brain. With the early examination of OSB, children can receive more effective treatment and support. Artificial intelligence methods are used in the field of health by examining and analyzing the medical data of patients, and they are used in the diagnosis phase and achieve successful results. In this study, models for the classification of OSB with ABCP and GP from Automatic Programming (AP) methods were produced and used for the analysis of attributes affecting OSB. According to the experimental results, both methods achieved a classification rate of about %90. In addition, the most necessary attributes for OSB classification were determined as gender, Q-Chat score, and facial expression inference.