Training the Machine Learning Programs to Measure the Arterial Phase and Identify the Types of Coronary Flow

Abstract

Coronary artery disease (CAD) is one of the most common and severe medical conditions worldwide. The current research focused on investigating the mechanisms and prevention of the detrimental effects of CAD. Recently, the principles and practices of fluid mechanics were used to explain the formation of CAD with the help of a new angiographic recording and reviewing technique. This new method focused on identifying the types of blood flows and their effects on the intima. To automate the process, an Artificial Intelligence program was utilized to support the investigators in reviewing coronary flow. This paper analyzes AI methods that assisted physician investigators in the measurement of the arterial phase and in the identification of the types of coronary flows.