Detection of myocardial ischemia by intracoronary ECG using convolutional neural networks.
<h4>Introduction</h4>The electrocardiogram (ECG) is a valuable tool for the diagnosis of myocardial ischemia as it presents distinctive ischemic patterns. Deep learning methods such as convolutional neural networks (CNN) are employed to extract data-derived features and to recognize natu...
Saved in:
Main Authors: | Marius Reto Bigler, Christian Seiler |
---|---|
Format: | article |
Language: | EN |
Published: |
Public Library of Science (PLoS)
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/535c46b521e84a38874ae6ea4fcff047 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Goosegrass Detection in Strawberry and Tomato Using a Convolutional Neural Network
by: Shaun M. Sharpe, et al.
Published: (2020) -
Automated detection of mouse scratching behaviour using convolutional recurrent neural network
by: Koji Kobayashi, et al.
Published: (2021) -
The stability of flow velocity and intracoronary resistance in the intracoronary electrocardiogram-triggered pressure ratio
by: Masafumi Nakayama, et al.
Published: (2021) -
Automated stomata detection in oil palm with convolutional neural network
by: Qi Bin Kwong, et al.
Published: (2021) -
Spectrum of clinical applications of interlead ECG heterogeneity assessment: From myocardial ischemia detection to sudden cardiac death risk stratification
by: Richard L. Verrier, et al.
Published: (2021)