Unraveling Phenotypic Heterogeneity in Stanford Type B Aortic Dissection Patients through Machine Learning Clustering Analysis of Cardiovascular CT Imaging

Aortic dissection remains a life-threatening condition necessitating accurate diagnosis and timely intervention. This study aimed to investigate phenotypic heterogeneity in patients with Stanford type B aortic dissection (TBAD) through machine learning clustering analysis of cardiovascular computed tomography (CT) imaging.