Open access
Jul 2026
A deep learning model for the interpretable identification of pulmonary thromboembolism from computed tomography pulmonary angiography
Utilizing the YOLOv11 architecture for automated CTPA analysis yields a highly sensitive and visually interpretable screening mechanism that holds substantial promise for reducing missed diagnoses and accelerating patient triage in acute clinical settings.
Yemei Li, Sunyu Chen, Guangkun Chen et al.
· Frontiers in Cardiovascular... · 0 citations