
Impact of machine-learning CT-derived fractional flow reserve for the diagnosis and management of coronary artery disease in the randomized CRESCENT trials
In this observational cohort study, the authors aimed to determine the potential impact of machine learning (ML) CT-derived fractional flow reserve (CT-FFR) on the diagnostic efficiency and effectiveness of coronary CT angiography (CCTA) in patients with obstructive coronary artery disease (CAD). It was found that the implementation of on-site CT-FFR may change management and help to improve diagnostic efficiency and