An Innovative Mathematical Approach Using Group Theory and Topology to Predict the Risks of Autism (Review)

Abstract

Through mathematical exploration group theory together with topology serves to forecast autistic tendencies in children. The research depends on persistent homology topology tools for analyzing complex brain pattern data alongside behavioral traits which occur in autistic children. Group theory provides a strong mathematical structure for understanding relationships within the data, helping to model and quantify connections in ways that traditional methods may miss.By applying topology, hidden patterns and associations in the data, which may not be evident through conventional analysis, can be identified and interpreted.These methods facilitate predictive modeling, offering earlier identification of children at risk of autism by analyzing data from brain images or behavioral observations.The goal of this approach is to create more accurate predictive models, enabling early medical intervention. Advanced mathematical tools through this approach improve medical diagnosis by permitting better interpretation of data for more effective results.