Using fuzzy neural networks for improving the prediction of children with autism through mobile devices

Mobile systems were built to aid in the prediction of children with autism traits. This type of system uses artificial intelligence capabilities and machine learning techniques to assign probabilities to people who undergo the test in the application. According to the information provided by the authors of the mobile application, it is intended to use fuzzy neural networks to aid in prediction whether or not the person has traits of autism. Therefore, this paper proposes the insertion of an interpretive technique based on an extreme learning machine to deal with questions provided by users seeking to obtain more immediate responses, based on binary classification labels. The tests performed with the base achieved high levels of accuracy for the proposed model and base, making it a viable alternative for the efficient prediction of children with autism.