A Spectrum of Cardiac Health Risk Assessment Intelligent System

Abstract

Medical diagnosis, particularly for cardiac conditions, is complex due to clinical variability, subjectivity, and incomplete information, which can lead to delays or errors. This article presents the development of an intelligent system using ECG data to enhance clinical efficiency, reduce diagnostic errors, and support medical decisionmaking. The system smoothly integrates into clinical workflows, analyzes complex data, and enhances patient outcomes. The Python programming language has been used to develop the code for this model.