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Classification of Autism Spectrum Disorder for Adolescents Using Artificial Neural Networks

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  • Sümeyye Çelik
  • Melike Şişeci Çeşmeli
  • İhsan Pençe
  • Özlem Çetinkaya Bozkurt

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.

Suggested Citation

  • Sümeyye Çelik & Melike Şişeci Çeşmeli & İhsan Pençe & Özlem Çetinkaya Bozkurt, 2022. "Classification of Autism Spectrum Disorder for Adolescents Using Artificial Neural Networks," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 10(1), pages 15-24, June.
    • Handle: RePEc:anm:alpnmr:v:10:y:2022:i:1:p:15-24
    DOI: https://doi.org/10.17093/alphanumeric.1031513
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    References listed on IDEAS

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    1. El-Bouri, Ahmed & Balakrishnan, Subramaniam & Popplewell, Neil, 2000. "Sequencing jobs on a single machine: A neural network approach," European Journal of Operational Research, Elsevier, vol. 126(3), pages 474-490, November.
    2. Sümeyye Çelik, 2020. "Determination and Classification of Importance of Attributes Used in Diagnosing Pregnant Women's Birth Method," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 8(2), pages 261-274, December.
    Full references (including those not matched with items on IDEAS)

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    2. Sümeyye Çelik, 2020. "Determination and Classification of Importance of Attributes Used in Diagnosing Pregnant Women's Birth Method," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 8(2), pages 261-274, December.
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    More about this item

    Keywords

    Adolescent Subset; Artificial Neural Networks; Autism Spectrum Disorder; Classification;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics

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