Prediction of Autism Severity Level in Bangladesh Using Fuzzy Logic: FIS and ANFIS

Ahsan, Rahbar; Chowdhury, Tauseef Tasin; Ahmed, Wasit; Mahia, Mahrin Alam; Mishma, Tahmin; Mishal, Mahbubur Rahman; Rahman, Rashedur M.

doi:10.1007/978-3-319-98678-4_22

Cited by 3 publications

(1 citation statement)

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“…In [10], the use of neural networks in the classification of autism has been studied. The authors of the article [11] have developed a new method which is based on the neuro-fuzzy network approach for classifying and predicting autism. The reason for the use of the fuzzy approach is also due to the uncertainty in the diagnosis and prediction of autism, which the research presented in this paper also emphasizes this issue.…”

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confidence: 99%

Autism Spectrum Diagnosis using Adaptive Learning Algorithm for Multiple MLP Classifier

Safara¹

2021

JISIoT

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A medical condition that causes disability and early neurological and cognitive condition is autism spectrum disorder (ASD). Gene expression and environment have an impact on this medical condition. Development of diagnostic instruments and skills improved the autism recognition and increased the society awareness about it. To cope with this disorder collaboration between families, service providers, and autistic individuals is a necessity. Early diagnosis of ASD could help in lessening stress, increase adaptation, and support welfare in healthcare systems. Therefore, a large body of research is attempting to provide an intelligent medical diagnostic system to identify and diagnose ASD in early stages using machine learning methods. In this paper, several multilayer perceptron neural network is proposed for ASD detection in healthcare systems. The learning rate is adaptively tuned to achieve the best results. The results show that the approach proposed in this study achieved 99.6% accuracy, which indicates the superiority of the proposed method in identifying and detecting autism disorder in comparison with similar previous methods.

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confidence: 99%