Can random forest algorithm predict CAD?

We compared the baseline and clinical characteristics between two groups. Then, Random Forest algorithm was used to construct a model to predict CAD and the model was assessed by receiver operating characteristic (ROC) curve.

What does CAD stand for?

Anyone you share the following link with will be able to read this content: The main goal driving this work is to develop computer-aided classification models relying on clinical data to identify coronary artery disease (CAD) instances with high accuracy while incorporating the expert’s opinion as input, making it a "man-in-the-loop" approach.

Can human expertise improve the diagnosis of CAD?

The results of this study demonstrate the potential for this approach to improve the diagnosis of CAD and highlight the importance of considering the role of human expertise in the development of computer-aided classification models.

Should ML algorithms be used to predict CAD instances?

Ideally, for healthy subjects, this procedure should be avoided. There is a plethora of related work 4, 5, 6, 7, 8, 9, 10 where common ML algorithms are used to predict CAD instances with varying results, ranging accuracy-wise from 71.1% to over 98% when also employing image data.