533 citations · 547 across the 6 of their papers we have counts for
17 papers
A Greedy Graph Search Algorithm Based on Changepoint Analysis for Automatic QRS Complex Detection
Atiyeh Fotoohinasab, Toby Hocking, Fatemeh Afghah
The electrocardiogram (ECG) signal is the most widely used non-invasive tool for the investigation of cardiovascular diseases. Automatic delineation of ECG fiducial points, in part…
A Graph-Constrained Changepoint Learning Approach for Automatic QRS-Complex Detection
Atiyeh Fotoohinasab, Toby Hocking, Fatemeh Afghah
This study presents a new viewpoint on ECG signal analysis by applying a graph-based changepoint detection model to locate R-peak positions. This model is based on a new graph lear…
An Uncertainty Estimation Framework for Risk Assessment in Deep Learning-based Atrial Fibrillation Classification
James Belen, Sajad Mousavi, Alireza Shamsoshoara +1
Atrial Fibrillation (AF) is among one of the most common types of heart arrhythmia afflicting more than 3 million people in the U.S. alone. AF is estimated to be the cause of death…
Multi-level Feature Learning on Embedding Layer of Convolutional Autoencoders and Deep Inverse Feature Learning for Image Clustering
Behzad Ghazanfari, Fatemeh Afghah
This paper introduces Multi-Level feature learning alongside the Embedding layer of Convolutional Autoencoder (CAE-MLE) as a novel approach in deep clustering. We use agglomerative…
Piece-wise Matching Layer in Representation Learning for ECG Classification
Behzad Ghazanfari, Fatemeh Afghah, Sixian Zhang
This paper proposes piece-wise matching layer as a novel layer in representation learning methods for electrocardiogram (ECG) classification. Despite the remarkable performance of…
ECG Language Processing (ELP): a New Technique to Analyze ECG Signals
Sajad Mousavi, Fatemeh Afghah, Fatemeh Khadem +1
A language is constructed of a finite/infinite set of sentences composing of words. Similar to natural languages, Electrocardiogram (ECG) signal, the most common noninvasive tool t…