Computational Frontiers in Arteriovenous Fistula Maturation: A Review of Fluid Dynamics and Machine Learning Models

This review investigates the mechanisms behind the high failure rates of arteriovenous (AV) fistula maturation in hemodialysis patients, which can reach up to 60%. The authors explore the potential of computational fluid dynamics (CFD) and machine learning (ML) models to better understand hemodynamic conditions and predict clinical outcomes, while highlighting the need for larger, more diverse datasets and external validation to enhance the clinical applicability of these models.