533 citations · 600 across the 20 of their papers we have counts for
9 papers · 1 filter
ECGBERT: Understanding Hidden Language of ECGs with Self-Supervised Representation Learning
Seokmin Choi, Sajad Mousavi, Phillip Si +3
In the medical field, current ECG signal analysis approaches rely on supervised deep neural networks trained for specific tasks that require substantial amounts of labeled data. Ho…
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…
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…
A Graph-constrained Changepoint Detection Approach for ECG Segmentation
Atiyeh Fotoohinasab, Toby Hocking, Fatemeh Afghah
Electrocardiogram (ECG) signal is the most commonly used non-invasive tool in the assessment of cardiovascular diseases. Segmentation of the ECG signal to locate its constitutive w…
SleepEEGNet: Automated Sleep Stage Scoring with Sequence to Sequence Deep Learning Approach
Sajad Mousavi, Fatemeh Afghah, U. Rajendra Acharya
Electroencephalogram (EEG) is a common base signal used to monitor brain activity and diagnose sleep disorders. Manual sleep stage scoring is a time-consuming task for sleep expert…
A Feature Selection Method Based on Shapley Value to False Alarm Reduction in ICUs, A Genetic-Algorithm Approach
Mohammad Zaeri-Amirani, Fatemeh Afghah, Sajad Mousavi
High false alarm rate in intensive care units (ICUs) has been identified as one of the most critical medical challenges in recent years. This often results in overwhelming the clin…