Machine learning-based identification of symptomatic carotid atherosclerotic plaques with dual-energy computed tomography angiography

This study aimed to develop and validate a machine learning model incorporating both dual-energy computed tomography (DECT) angiography quantitative parameters and clinically relevant risk factors for the identification of symptomatic carotid plaques to prevent acute cerebrovascular events.
Source: Journal of Stroke and Cerebrovascular Diseases - Category: Neurology Authors: Source Type: research