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Category: Project

Description: Exposure to risk factors during the perinatal phase has been shown to lead to negative and lasting impacts on child development with consequences for the whole individual lifespan and for society in general. Given the importance of identifying early markers within highly complex and heterogeneous perinatal factors, machine learning techniques appear as a promising tool. The current scoping review serves two main aims: (1) to summarize the evidence focusing on the application of machine learning techniques in predicting a child’s development based on perinatal risk factors; (2) to conduct a critical appraisal and evaluate various aspects, including representativeness, data leakage, validation, performance metrics, and interpretability.