AI-Based Facial Dysmorphism Assessment in Diverse Populations: Advancements and Future Directions.

Abstract

The recent study by Makay et al. significantly advances our understanding of artificial intelligence (AI)-based tools for evaluating facial dysmorphism, particularly within underrepresented populations such as Central African children. This commentary underscores the importance of integrating AI phenotyping technologies with traditional clinical assessments, emphasizing their complementary roles rather than replacement. The commentary further explores methodological enhancements, including the integration of three-dimensional facial analysis, and highlights the necessity for ongoing validation studies in diverse ethnic cohorts to optimize algorithmic precision and clinical applicability. These refinements are essential for improving dysmorphology evaluations globally, particularly in regions with limited genetic healthcare resources.