Cognitive Measures in Developmental Language Disorder Classification in Monolingual and Bilingual Children: A Machine Learning Approach

Puntos clave

• Classification models identified key cognitive measures for diagnosing developmental language disorder in children.
• The study achieved an accuracy of 85% in classifying bilingual and monolingual children.
• Assessment employed a machine learning approach to analyze cognitive measures across diverse language backgrounds.
• These findings support enhanced diagnostic strategies for developmental language disorders, warranting further investigation.