Machine Learning Driven Framework to Predict the Intellectual Disability

Intellectual Disability (ID) is a condition that greatly hinders cognitive capacities, hence restricting an individual’s capacity to operate in their daily life. Certain folks necessitate enduring assistance and aid, however others may only encounter negligible effects on their way of life. Timely identification of ID is crucial to provide suitable interventions for persons impacted by this disease. Artificial intelligence has the ability to diagnose identification through many approaches, such as evaluating natural behavior, undertaking visual observation, and using machine learning (ML) to determine identity based on distinguishing traits. This study introduces a ML-enabled framework that effectively identifies the ID based on input features. The architecture is evaluated by utilizing four machine learning models to measure performance using statistical metrics. Moreover, AutoML methodologies are employed to optimize the performance of the proposed system. Furthermore, highlight the potential path for another researcher to employ and apply this methodology.