Cardiologist-level arrhythmia detection with convolutional neural networks
We develop an algorithm which exceeds the performance of board certified cardiologists in
detecting a wide range of heart arrhythmias from electrocardiograms recorded with a single�…
detecting a wide range of heart arrhythmias from electrocardiograms recorded with a single�…
Comparing feature-based classifiers and convolutional neural networks to detect arrhythmia from short segments of ECG
F Andreotti, O Carr, MAF Pimentel…�- 2017 computing in�…, 2017 - ieeexplore.ieee.org
The diagnosis of cardiovascular diseases such as atrial fibrillation (AF) is a lengthy and
expensive procedure that often requires visual inspection of ECG signals by experts. In�…
expensive procedure that often requires visual inspection of ECG signals by experts. In�…
Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network
Computerized electrocardiogram (ECG) interpretation plays a critical role in the clinical ECG
workflow. Widely available digital ECG data and the algorithmic paradigm of deep learning�…
workflow. Widely available digital ECG data and the algorithmic paradigm of deep learning�…
Combining deep neural networks and engineered features for cardiac arrhythmia detection from ECG recordings
Objective: We aim to combine deep neural networks and engineered features (hand-crafted
features based on medical domain knowledge) for cardiac arrhythmia detection from short�…
features based on medical domain knowledge) for cardiac arrhythmia detection from short�…
Cardiac arrhythmia detection using deep learning: A review
Due to its simplicity and low cost, analyzing an electrocardiogram (ECG) is the most
common technique for detecting cardiac arrhythmia. The massive amount of ECG data�…
common technique for detecting cardiac arrhythmia. The massive amount of ECG data�…
Accurate deep neural network model to detect cardiac arrhythmia on more than 10,000 individual subject ECG records
Background and objective Cardiac arrhythmia, which is an abnormal heart rhythm, is a
common clinical problem in cardiology. Detection of arrhythmia on an extended duration�…
common clinical problem in cardiology. Detection of arrhythmia on an extended duration�…
Beat by beat: Classifying cardiac arrhythmias with recurrent neural networks
With tens of thousands of electrocardiogram (ECG) records processed by mobile cardiac
event recorders every day, heart rhythm classification algorithms are an important tool for the�…
event recorders every day, heart rhythm classification algorithms are an important tool for the�…
Cardiac arrhythmia detection from ECG combining convolutional and long short-term memory networks
Objectives: Atrial fibrillation (AF) is a common heart rhythm disorder associated with deadly
and debilitating consequences including heart failure, stroke, poor mental health, reduced�…
and debilitating consequences including heart failure, stroke, poor mental health, reduced�…
[HTML][HTML] Multi-task deep learning for cardiac rhythm detection in wearable devices
J Torres-Soto, EA Ashley�- NPJ digital medicine, 2020 - nature.com
Wearable devices enable theoretically continuous, longitudinal monitoring of physiological
measurements such as step count, energy expenditure, and heart rate. Although the�…
measurements such as step count, energy expenditure, and heart rate. Although the�…
Usefulness of machine learning-based detection and classification of cardiac arrhythmias with 12-lead electrocardiograms
Background Deep-learning algorithms to annotate electrocardiograms (ECGs) and classify
different types of cardiac arrhythmias with the use of a single-lead ECG input data set have�…
different types of cardiac arrhythmias with the use of a single-lead ECG input data set have�…