Enhancing heart disease prediction with stacked ensemble and MCDM-based ranking: an optimized RST-ML approach

The findings demonstrate the effectiveness of the RST-ML framework in improving HD prediction accuracy. The successful application to diverse datasets indicates strong scalability and generalization potential, making the framework a robust and scalable solution for timely diagnosis across various health conditions.