Can ml predict CAD?

Using an ML approach provides the ability to predict the presence of CAD with high accuracy and recall, and thus allows practitioners to practice preventative medicine in patients with CAD in a timelier manner. However, at such initial stages, it should be noted that ML serves solely as a predictor of CAD rather than a diagnostic tool.

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.

Can advanced image-derived data predict long-term cardiovascular events?

Methods and analysis GeoCAD is a retrospective cohort study in 1000 adult patients who have undergone CTCA for investigation of suspected CAD. It is a proof-of-concept study to test the hypothesis that advanced image-derived patient-specific data can accurately predict long-term cardiovascular events.

Can machine learning improve CAD predictive ability?

Because machine learning utilizes datasets of patients who have already been diagnosed, the predictive ability of an ML algorithm for CAD would improve as more data are supplied to the algorithm.