Can a multimodal data-driven explainable prognostic model predict major adverse cardiovascular events in patients with unstable angina and heart failure with preserved ejection fraction?
A novel machine learning prognostic model provides a web-based tool to predict MACE in patients with concurrent HFpEF and unstable angina.
We developed a surv.xgboost.cox-based predictive model for MACEs in patients with the dual phenotype of HFpEF and UA. We implemented this model as a web-based calculator to facilitate clinical application.
Wang et al. (Mon,) studied this question.