Which model predicts high-risk CAD?

The model (C statistic, 0.75) was a better predictor of high-risk CAD compared with both the Pooled Cohort Equation (PCE; C statistic, 0.70; χ 2 =18.18; P <0.0001) 21 and modified Diamond-Forrester risk score (mDFS), aimed at symptomatic chest pain patients (C statistic, 0.68; χ 2 =26.90; P <0.0001).

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.

Is timely detection of CAD a risk factor?

Although CAD is both widely prevalent and may lead to fatal consequences, timely detection of CAD would empower clinicians to treat modifiable risk factors associated with the progression of CAD.