Memory classifiers combine standard deep neural network training with a domain knowledge-guided similarity metric to boost the robustness of classifiers. We�...

Jul 21, 2023 � In this paper, we show that using memory classifiers it is possible to attain a boost in robustness using expert-informed features. Memory�...

Abstract—The development of sophisticated machine learn- ing algorithms has made it possible to detect critical health conditions like cardiac arrhythmia,�...

It is shown that using memory classifiers it is possible to attain a boost in robustness using expert-informed features, and this approach improves the�...

Bibliographic details on Memory Classifiers for Robust ECG Classification against Physiological Noise.

Oct 25, 2021 � We conclude that physiological ECG noise impacts classification using deep learning methods and careful consideration should be given to the inclusion of noisy�...

This paper proposes a novel network Channel Activation Suppression with Lipschitz Constraints Net (CASLCNet), which employs the Channel-wise Activation�...

Mar 15, 2024 � In this review, we first discuss the current state-of-the-art AI models utilized for ECG-based cardiac rhythm classification.

It is concluded that physiological ECG noise impacts classification using deep learning methods and careful consideration should be given to the inclusion�...

In this review, we first discuss the current state-of-the-art AI models utilized for ECG-based cardiac rhythm classification.