Res. Assist., Department of Management Information Systems, Faculty of Business Administration Adana Alparslan Türkeş Science and Technology University, Adana, Turkiye, sumeyyecelik@atu.edu.tr
Assist. Prof., Department of Software Engineering, Computer Sciences, Faculty of Technology Mehmet Akif Ersoy University, Burdur, Turkiye, melikesiseci@mehmetakif.edu.tr
Assist. Prof., Department of Software Engineering, Computer Sciences, Faculty of Technology Mehmet Akif Ersoy University, Burdur, Turkiye, ihsanpence@mehmetakif.edu.tr
Artificial neural networks, is one of the most preferred artificial intelligence techniques in the modeling of complex systems today and the models are based on the working structure of the nerve cells in the human brain. Autism spectrum disorder is a complex neuro-developmental disorder that is congenital or occurs at an early age. Since early diagnosis has a very important role in the treatment, there are many studies on this subject. In this study, a subset of current autism spectrum disorder data obtained from UCI machine learning repository for adolescents has used. In order to test the success of the model, after the necessary preprocesses have performed on the data set, the data has separated into training and test set and classified with the trained network. As a result, 100% accuracy rate in the training set and 96.77% accuracy rate in the test set are achieved. Sensitivity, Specificity and F-measure values obtained in the test set are 0.94, 1.0 and 0.97, respectively and reveals the model success.
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2022
Çelik, S.,
Şişeci Çeşmeli, M.,
Pençe, İ.,
Çetinkaya Bozkurt, Ö.
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