Towards Transparent AI in Medicine: ECG-Based Arrhythmia Detection with Explainable Deep Learning
Technologies, Vol. 13, No. 1, pp. 34
Abstract
This paper presents a novel approach for arrhythmia detection based on electrocardiogram (ECG) that incorporates explainable artificial intelligence through an arrhythmia classification method utilizing a modified convolutional neural network (CNN) architecture. The study achieved an accuracy of 99.43%, with F1-scores approaching 100% for major arrhythmia classes using the MIT-BIH database.
Citation
Pavlo Radiuk, Liliana Klymenko, Iurii Krak. "Towards Transparent AI in Medicine: ECG-Based Arrhythmia Detection with Explainable Deep Learning". Technologies, Vol. 13, No. 1, pp. 34, 2025.