Applications of machine learning methods to parent-child interaction data: A scoping review

Le résumé fourni par la source

The present scoping review aims to (1) systematically map machine learning (ML) applications to automated coding of parent-child observational data; (2) describe the behavioral constructs, the interaction tasks most frequently employed, and the populations studies; (3) characterize the performance of such ML approaches; and (4) identify key methodological gaps and priorities for advancing this field.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.