A Multimodal and Explainable Machine Learning Approach to Diagnosing Multi-Class Ejection Fraction from Electrocardiograms

This research developed a multimodal machine-learning framework combining ECG features and EHR data to diagnose multi-class left ventricular ejection fraction. The model achieved high AUROCs and used SHAP for explainability, outperforming baseline models.