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Dergiler / Alphanumeric Journal / 2022 / Cilt: 10 - Sayı: 1

Classification of Autism Spectrum Disorder for Adolescents Using Artificial Neural Networks

Özlem ÇETİNKAYA BOZKURT
Sümeyye ÇELİK
İhsan PENÇE
Melike ŞİŞECİ ÇEŞMELİ
Sayfa
15–24
Yayın Tarihi
2022-10-11
DOI
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Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

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.

📌 3 Maddede Bu Makale

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Amaç & Hipotez: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.
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Temel Bulgular & Veri: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.
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Sonuç & Katkı: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.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Alan Parametreleri

Abstract

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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Bu Makaleye Atıf Yap

BOZKURT, Ö. Ç., ÇELİK, S., PENÇE, İ., ÇEŞMELİ, M. Ş. (2022). Classification of Autism Spectrum Disorder for Adolescents Using Artificial Neural Networks. Alphanumeric Journal, Cilt: 10 - Sayı: 1, 15–24. https://ajindex.com/articles/435085

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