3 citations · 3 across the 5 of their papers we have counts for
5 papers
Investigating ECG Diagnosis with Ambiguous Labels using Partial Label Learning
Sana Rahmani, Javad Hashemi, Ali Etemad
Label ambiguity is an inherent and largely unaddressed challenge in real-world electrocardiogram (ECG) diagnosis, arising from overlapping conditions and diagnostic disagreements.…
Uncertainty-Aware Multi-view Arrhythmia Classification from ECG
Mohd Ashhad, Sana Rahmani, Mohammed Fayiz +2
We propose a deep neural architecture that performs uncertainty-aware multi-view classification of arrhythmia from ECG. Our method learns two different views (1D and 2D) of single-…
Subject Representation Learning from EEG using Graph Convolutional Variational Autoencoders
Aditya Mishra, Ahnaf Mozib Samin, Ali Etemad +1
We propose GC-VASE, a graph convolutional-based variational autoencoder that leverages contrastive learning for subject representation learning from EEG data. Our method successful…
Dynamic Prototype Rehearsal for Continual ECG Arrhythmia Detection
Sana Rahmani, Reetam Chatterjee, Ali Etemad +1
Continual Learning (CL) methods aim to learn from a sequence of tasks while avoiding the challenge of forgetting previous knowledge. We present DREAM-CL, a novel CL method for ECG…
Analysis of Augmentations for Contrastive ECG Representation Learning
Sahar Soltanieh, Ali Etemad, Javad Hashemi
This paper systematically investigates the effectiveness of various augmentations for contrastive self-supervised learning of electrocardiogram (ECG) signals and identifies the bes…