Journal of Intelligent Systems and Internet of Things JISIoT 2690-6791 2769-786X 10.54216/JISIoT https://www.americaspg.com/journals/show/729 2019 2019 School of Transportation, Southeast University, Nanjing, 211189, China Qiang Qiang Department of Computer Engineering, Islamshahr Branch, Islamic Azad University, Islamshahr, Iran Fatemeh Safara 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. 2021 2021 33 44 10.54216/JISIoT.020201 https://www.americaspg.com/articleinfo/18/show/729