Detection of Autistic Spectrum Disorder Using Artificial Neural Network
Yıl: 2023 Cilt: 23 Sayı: 4 Sayfa Aralığı: 955 - 961 Metin Dili: İngilizce DOI: 10.35414/akufemubid.1239360 İndeks Tarihi: 04-01-2024
Detection of Autistic Spectrum Disorder Using Artificial Neural Network
Öz: Autistic Spectrum Disorder (ASD) is a neuro-developmental disorder that is congenital or manifests with a delay in social relations and physiological development at an early age, and also causes problems in communication. It is possible to reduce the effect of the disease on individuals with early diagnosis. However, detecting ASD at an early age requires time and cost. In the studies conducted in recent years, it is seen that there is a serious increase in ASD cases. In order to prevent this increase, decision support systems should be established for early diagnosis. It is important to develop decision support models to diagnose ASD, especially for children aged 12-36 months. In this study, a model was developed that can help in detecting ASD with high accuracy for 12-36 months old children. The data set used in the created model was collected from the mobile application named ASDTests developed by Thabtah. In the estimation phase, four different machine learning algorithms which are support vector machine, Naive Bayes,Random Forest and Artificial Neural Network were used. In the classification process, high success rate was obtained with artificial neural network, random forest classifier.
Anahtar Kelime: Otistik Spectrum Bozukluğunun Yapay Sinir Ağları ile Tespiti
Öz: Otistik Spektrum Bozukluğu (OSB), doğuştan gelen yada yaşamın ilk yaşlarında sosyal ilişkilerde ve fizyolojik gelişimde gecikme ile kendini gösteren ve aynı zamanda iletişimde sorunlara neden olan nöro-gelişimsel bir bozukluktur. Hastalığın bireyler üzerinde etkisinin erken tanı ile azaltılması mümkündür. Ancak OSB’yi erken yaşta tespit etmek zaman ve maliyet gerektirmektedir. Son yıllarda yapılan çalışmalarda OSB vakalarında ciddi bir artış olduğu görülmektedir. Bu artışı önlemek için erken tanı için karar destek sistemleri oluşturulmalıdır. Özellikle 12-36 aylık çocuklar için OSB tanısı koymak için karar destek modellerinin geliştirilmesi önem taşımaktadır. Bu çalışmada 12-36 aylık çocuklar için yüksek doğrulukta OSB tespitinde yardımcı olabilecek bir model geliştirilmiştir. Oluşturulan modelde kullanılan veri seti Thabtah tarafından geliştirilen ASDTests isimli mobil uygulamadan toplanmıştır. Tahminleme aşamasında destek vektör makinesi, Naive Bayes, rasgele orman , yapay sinir ağları olmak üzere dört farklı makine öğrenimi algoritması kullanılmıştır. Sınıflandırma sürecinde yapay sinir ağları, rasgele orman sınıflandırıcı ile yüksek başarı oranı elde edilmiştir.
Anahtar Kelime: Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık
- Al-Diabat, M, 2018. Fuzzy data mining for autism classification of children. Int. J. Adv. Comput. Sci. Appl., 9. Baranwal, A. and Vanitha, M., 2020. Autistic spectrum disorder screening: prediction with machine learning models. In 2020 International conference on emerging trends in information technology and engineering,1-7.
- Beykikhoshk, A., Arandjelovi´, O., Phung, D., Venkatesh, S., and Caelli, T. ,2014. Data-mining twitter and the autism spectrum disorder: 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014) , 349 – 356
- Breiman, L., 2001.Random forests. Machine learning, 45, 5-32.
- Catania, L. J., 2021. AI applications in prevalent diseases and disorders. Foundations of Artificial Intelligence in Healthcare and Bioscience, Elsevier, 293-444.
- Cordova, M., Shada, K., Demeter, D. V., Doyle, O., Miranda-Dominguez, O., Perrone, A., and Feczko, E. ,2020. Heterogeneity of executive function revealed by a functional random forest approach across ADHD and ASD. NeuroImage: Clinical, 26, 102245.
- Cortes, C. and Vapnik, 1995. V. Support-vector networks. Mach Learn 20, 273–297 Duda, M., Ma, R., Haber, N., and Wall, D., 2016. Use of machine learning for behavioural distinction of autism. Translational Psychiatry, 221.
- Erkan, U. and Thanh, D. , 2019. Autism spectrum disorder detection with machine learning methods. Current Psychiatry Research and Reviews Formerly,15, 297-308.
- Gultekin, M. , and Kalipsiz, O., 2019. Story Point-Based Effort Estimation Model with Machine Learning Techniques, Int'l Journal of Software Engineering and Knowledge Engineering.
- Hadi W., Issa G., Ishtaiwi A. ACPRISM, 2017. Associative classification based on PRISM algorithm. Inf. Sci. (NY), 417 , 287-300
- Metlek, S. and Kayaalp, K., 2020. Otistik Spektrum Bozukluğunun Makine Öğrenme Algoritmaları ile Tespiti. Journal of Intelligent Systems: Theory and Applications, 3.2 , 60-68.
- Mohanty, A. S., Parida, P. and Patra, K. C. ,2021. ASD Classification for Children using Deep Neural Network. Global Transitions Proceedings, 2, 461-466
- Mohanty, A. S., Parida, P. and Patra, K. C., 2021. Identification of autism spectrum disorder using deep neural network. In Journal of Physics: Conference Series , 1, 012006.
- Nayeem, M. J., Rana, S., Alam, F., and Rahman, M. A., 2021. Prediction of Hepatitis Disease Using K-Nearest Neighbors, Naive Bayes, Support Vector Machine, Multi-Layer Perceptron and Random Forest. 2021 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD), 280-284.
- Nasser, Ibrahim M.; Al-Shawwa and Mohammed O.; Abu-Naser, Samy S. Artificial neural network for diagnose autism spectrum disorder. 2019.
- Negin, F., Ozyer, B., Agahian, S., Kacdioglu, S., Ozyer, G. T. ,2021. Vision-assisted recognition of stereotype behaviors for early diagnosis of Autism Spectrum Disorders. Neurocomputing, 446, 145-155.
- Nielsen, J. A., Zielinski, B. A., Fletcher, P. T., Alexander, A. L., Lange, N., Bigler, E. D. and Anderson, J. S. ,2013. Multisite functional connectivity MRI classification of autism: ABIDE results. Frontiers in human neuroscience, 7, 599.
- Nishat, M. M., Hasan, T., Nasrullah, S. M., Faisal, F., Asif, M. A. A. R., and Hoque, M. A, 2021. Detection of Parkinson's disease by employing boosting algorithms. In 2021 Joint 10th International Conference on Informatics, Electronics & Vision (ICIEV) and 2021 5th International Conference on Imaging, Vision & Pattern Recognition (icIVPR), 1-7.
- Omar, K. S., Mondal, P., Khan, N. S., Rizvi, M. R. K. and Islam, M. N., 2019. A Machine Learning Approach to Predict Autism Spectrum Disorder. 2019 International Conference on Electrical, Computer and Communication Engineering(ECCE), 1-6.
- Rabbi, M. F., Hasan, S. M., Champa, A. I., and Zaman, M. A. , 2021 A convolutional neural network model for early-stage detection of autism spectrum disorder. In: 2021 international conference on information and communication technology for sustainable development (icict4sd). IEEE, 110-114.
- Tapak L., Afshar S., Afrasiabi M., Ghasemi M.K. and Alirezaei P., 2021. Applicaiton of Genetic Algorithm-Based Support Vector Machine in Identification of Gene Expression Signatures for Psoriasis Classification. Biomed Research International, 10.
- Thabtah, F., 2019. An accessible and efficient autism screening method for behavioural data and predictive analyses, Health informatics journal 25(4), 1739-1755.
- Virendra S. Dahe, Sai G. Manikandan, Jegadeeshwaran R., Sakthivel G. and Lakshmipathi J, 2021. Tool condition monitoring using Random forest and FURIA through statistical learning Mater. Today Proc., 46 ,1161-1166.
- Shahamiri, S. R., and Thabtah, F. ,2020. Autism AI: a new autism screening system based on artificial intelligence. Cognitive Computation, 12(4), 766-777.
- Vaishali, R., and Sasikala R., 2018. A machine learning based approach to classify autism with optimum behaviour sets, International Journal of Engineering & Technology 7(4) , 18.
- https://www.cdc.gov/ncbddd/autism/facts.html, (09.12.2022)
- http://fadifayez.com/publications/#datasets, (07.07.2017)
- https://www.kaggle.com/datasets/fabdelja/autism-screening-for-toddlers (06.2018)
| APA | Özdemir Ş, Yıldız K (2023). Detection of Autistic Spectrum Disorder Using Artificial Neural Network. , 955 - 961. 10.35414/akufemubid.1239360 |
| Chicago | Özdemir Şeyma Nur,Yıldız Kazım Detection of Autistic Spectrum Disorder Using Artificial Neural Network. (2023): 955 - 961. 10.35414/akufemubid.1239360 |
| MLA | Özdemir Şeyma Nur,Yıldız Kazım Detection of Autistic Spectrum Disorder Using Artificial Neural Network. , 2023, ss.955 - 961. 10.35414/akufemubid.1239360 |
| AMA | Özdemir Ş,Yıldız K Detection of Autistic Spectrum Disorder Using Artificial Neural Network. . 2023; 955 - 961. 10.35414/akufemubid.1239360 |
| Vancouver | Özdemir Ş,Yıldız K Detection of Autistic Spectrum Disorder Using Artificial Neural Network. . 2023; 955 - 961. 10.35414/akufemubid.1239360 |
| IEEE | Özdemir Ş,Yıldız K "Detection of Autistic Spectrum Disorder Using Artificial Neural Network." , ss.955 - 961, 2023. 10.35414/akufemubid.1239360 |
| ISNAD | Özdemir, Şeyma Nur - Yıldız, Kazım. "Detection of Autistic Spectrum Disorder Using Artificial Neural Network". (2023), 955-961. https://doi.org/10.35414/akufemubid.1239360 |
| APA | Özdemir Ş, Yıldız K (2023). Detection of Autistic Spectrum Disorder Using Artificial Neural Network. Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, 23(4), 955 - 961. 10.35414/akufemubid.1239360 |
| Chicago | Özdemir Şeyma Nur,Yıldız Kazım Detection of Autistic Spectrum Disorder Using Artificial Neural Network. Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi 23, no.4 (2023): 955 - 961. 10.35414/akufemubid.1239360 |
| MLA | Özdemir Şeyma Nur,Yıldız Kazım Detection of Autistic Spectrum Disorder Using Artificial Neural Network. Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, vol.23, no.4, 2023, ss.955 - 961. 10.35414/akufemubid.1239360 |
| AMA | Özdemir Ş,Yıldız K Detection of Autistic Spectrum Disorder Using Artificial Neural Network. Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi. 2023; 23(4): 955 - 961. 10.35414/akufemubid.1239360 |
| Vancouver | Özdemir Ş,Yıldız K Detection of Autistic Spectrum Disorder Using Artificial Neural Network. Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi. 2023; 23(4): 955 - 961. 10.35414/akufemubid.1239360 |
| IEEE | Özdemir Ş,Yıldız K "Detection of Autistic Spectrum Disorder Using Artificial Neural Network." Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, 23, ss.955 - 961, 2023. 10.35414/akufemubid.1239360 |
| ISNAD | Özdemir, Şeyma Nur - Yıldız, Kazım. "Detection of Autistic Spectrum Disorder Using Artificial Neural Network". Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi 23/4 (2023), 955-961. https://doi.org/10.35414/akufemubid.1239360 |
