New Findings from Medical University of South Carolina Describe Advances in Machine Learning (Impact of Machine-learning-based Coronary Computed Tomography Angiography-derived Fractional Flow Reserve On Decision-making In Patients With Severe ...)

摘要

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Research findings on Machine Learning are discussed in a new report. According to news reporting out of Charleston, South Carolina, by NewsRx editors, research stated, “To evaluate feasibility and diagnostic performance of coronary CT angiography (CCTA)-derived fractional flow reserve (CT-FFR) for detection of significant coronary artery disease (CAD) and decision-making in patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR) to potentially avoid additional pre-TAVR invasive coronary angiography (ICA). Consecutive patients with severe AS (n = 95, 78.6 +/- 8.8 years, 53% female) undergoing pre-procedural TAVR-CT followed by ICA with quantitative coronary angiography were retrospectively analyzed.”