Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
Low-cost wearables with capability to record electrocardiograms (ECG) are becoming increasingly available. These wearables typically acquire single-lead ECGs that are mainly used for screening of cardiac arrhythmias such as atrial fibrillation. Most ...
The field of cardiac electrophysiology (EP) had adopted simple artificial intelligence (AI) methodologies for decades. Recent renewed interest in deep learning techniques has opened new frontiers in electrocardiography analysis including signature id...
Studies in health technology and informatics
Sep 21, 2021
Automatic electrocardiogram (ECG) analysis has been one of the very early use cases for computer assisted diagnosis (CAD). Most ECG devices provide some level of automatic ECG analysis. In the recent years, Deep Learning (DL) is increasingly used for...
There has been an exponential growth of artificial intelligence (AI) and machine learning (ML) publications aimed at advancing our understanding of atrial fibrillation (AF), which has been mainly driven by the confluence of two factors: the advances ...
European heart journal. Cardiovascular pharmacotherapy
Sep 1, 2020
AIMS: Most clinical risk stratification models are based on measurement at a single time-point rather than serial measurements. Artificial intelligence (AI) is able to predict one-dimensional outcomes from multi-dimensional datasets. Using data from ...
OBJECTIVE: Electrical cardioversion is frequently performed to restore sinus rhythm in patients with persistent atrial fibrillation (AF). However, AF recurs in many patients and identifying the patients who benefit from electrical cardioversion is di...
The adoption of wearables in medicine has rapidly expanded worldwide. New generations of wearables are emerging, driven by consumers' demand to monitor their own health. With the ongoing development of new features capable of assessing real-time biom...
BACKGROUND: Detection of atrial fibrillation (AF) occurrence over a long duration has been a challenge in the screening and follow-up of AF patients. Wearable devices may be an ideal solution.
This study uses video and a pretrained deep convolutional neural network to analyze facial photoplethysmographic signals in detection of atrial fibrillation.