AI analysis for ejection fraction estimation from 12-lead ECG
Published in Scientific Reports, 2025
This study investigates the use of 12-lead ECG signals to estimate heart ejection fraction (EF) in a rural Appalachian population. Using a range of machine learning and deep learning models—including Transformers—our analysis shows deep learning models achieve the highest performance (AUROC ~0.86), with specific multi-lead combinations improving accuracy and model interpretability providing insights into predictive features.
Citation: Devkota, A., Prajapati, R., El-Wakeel, A., Adjeroh, D., Patel, B. and Gyawali, P., 2025. AI analysis for ejection fraction estimation from 12-lead ECG. Scientific Reports, 15(1), p.13502.
Citation: Devkota, A., Prajapati, R., El-Wakeel, A., Adjeroh, D., Patel, B. and Gyawali, P., 2025. AI analysis for ejection fraction estimation from 12-lead ECG. Scientific Reports, 15(1), p.13502.
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