533 citations · 534 across the 4 of their papers we have counts for
10 papers
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…
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…
HAN-ECG: An Interpretable Atrial Fibrillation Detection Model Using Hierarchical Attention Networks
Sajad Mousavi, Fatemeh Afghah, U. Rajendra Acharya
Atrial fibrillation (AF) is one of the most prevalent cardiac arrhythmias that affects the lives of more than 3 million people in the U.S. and over 33 million people around the wor…
An Autonomous Spectrum Management Scheme for Unmanned Aerial Vehicle Networks in Disaster Relief Operations
Alireza Shamsoshoara, Fatemeh Afghah, Abolfazl Razi +3
This paper studies the problem of spectrum shortage in an unmanned aerial vehicle (UAV) network during critical missions such as wildfire monitoring, search and rescue, and disaste…
Single-modal and Multi-modal False Arrhythmia Alarm Reduction using Attention-based Convolutional and Recurrent Neural Networks
Sajad Mousavi, Atiyeh Fotoohinasab, Fatemeh Afghah
This study proposes a deep learning model that effectively suppresses the false alarms in the intensive care units (ICUs) without ignoring the true alarms using single- and multimo…
An Unsupervised Feature Learning Approach to Reduce False Alarm Rate in ICUs
Behzad Ghazanfari, Fatemeh Afghah, Kayvan Najarian +3
The high rate of false alarms in intensive care units (ICUs) is one of the top challenges of using medical technology in hospitals. These false alarms are often caused by patients'…