Investigating the accuracy and sensitivity of the intelligent screener system to predict children at risk of neurodevelopmental disorders (attention deficit-hyperactivity disorder and dyslexia)

The aim of this research was toinvestigate the accuracy, sensitivity and specificity of the designed intelligent screener system to predict pre-schoolers at risk of common neurodevelopmental disorders (attention deficit-hyperactivity disorder and dyslexia). For data collection, survey research method of evaluation and diagnosis was used.To do so, preschool children were selected by random cluster sampling and the computerized neuro-cognitive program designed by Delavarian et al. was applied for data collection. The data related to each sample was saved for two years, until the definite diagnosis was determined. These data was applied in designing an intelligent screener. Multilayer perceptron artificial neural network was appliedfor designing this screener. Finally, the average accuracy of this intelligent screener obtained 94 % and the sensitivity and specificity in screening at risk pre-schoolers reached 93.45% and 95.27%, respectively. According to the acquired high accuracy, sensitivity and specificity, this screener could be used in prediction of pre-schoolers at risk of the mentioned disorders before entering to elementary school.