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Journals / 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
Pages
15–24
Publication Date
2022-10-11
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

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 Key Takeaways

🎯
Objective & Hypothesis: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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Key Findings & Data: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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Conclusion & Impact: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.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

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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Cite This Article

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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