PGAE-ICA: A simplified digital system for intellectual measurement-assessment in children and adolescents using cognitive testing and machine learning techniques

Measuring and assessing intelligence level in children and adolescents is crucial for monitoring their developmental progress, identifying intellectual disabilities, and implementing early interventions. To date, there is no digital and simplified tool specifically designed to evaluate whether intelligence is normal or abnormal in these age stages. The present study aims to develop an intelligence measurement-assessment system based on primary cognitive ability tests across four cognitive domains and a machine learning model to distinguish between normal and abnormal intelligence. A total of 103 participants aged 9 to 17, were recruited for this study, including 39 with abnormal intelligence and 64 with normal intelligence. Participants completed the Chinese Wechsler Intelligence Scale for Children and primary cognitive ability tests in a randomly counterbalanced order. Independent samples t-tests and partial correlation analyses were employed to validate whether the cognitive tests effectively reflected individual differences in intelligence and to examine the correlation between cognitive tests and intelligence, while excluding ineffective tests. A genetic algorithm-optimized extreme learning machine model was then constructed and trained to predict intellectual status of children and adolescents. The results indicated that after excluding the time selection task, the remaining eleven cognitive tests effectively reflected the differences between individuals with normal and abnormal intelligence, with significant positive correlations to intelligence. Meanwhile, the optimized extreme learning machine model achieved an overall prediction accuracy rate of 92.63%, outperforming the unoptimized basic extreme learning machine model as well as traditional logistic regression model and support vector machine model. Therefore, the validity of the digital and simplified intelligence measurement-assessment system for children and adolescents, named PGAE-ICA, developed in the present study has been confirmed, supporting its further application in clinical and scientific research fields. Furthermore, the PGAE-ICA establishes a foundation for the future development of artificial intelligence expert diagnostic systems for identifying intellectual abnormalities.