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 single-lead ECG recordings.
IEEE journal of biomedical and health informatics
May 29, 2019
Automatic classification of electrocardiogram (ECG) signals is important for diagnosing heart arrhythmias. A big challenge in automatic ECG classification is the variation in the waveforms and characteristics of ECG signals among different patients. ...
Computer methods and programs in biomedicine
May 10, 2019
BACKGROUND AND OBJECTIVE: For diagnosis of arrhythmic heart problems, electrocardiogram (ECG) signals should be recorded and monitored. The long-term signal records obtained are analyzed by expert cardiologists. Devices such as the Holter monitor hav...
The interpretation of various cardiovascular blood flow abnormalities can be identified using Electrocardiogram (ECG). The predominant anomaly due to the blood flow dynamics leads to the occurrence of cardiac arrhythmias in the cardiac system. In thi...
The aim of this study is to design GoogLeNet deep neural network architecture by expanding the kernel size of the inception layer and combining the convolution layers to classify the electrocardiogram (ECG) beats into a normal sinus rhythm, premature...
This work reports a multilead interval measurement algorithm for a high-resolution digital electrocardiograph. The software enables off-line ECG processing including detection as well as an accurate multilead interval detection algorithm using sup...
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 present an opportunity to substantially improve the accuracy and s...
Abnormality of the cardiac conduction system can induce arrhythmia - abnormal heart rhythm - that can frequently lead to other cardiac diseases and complications, and are sometimes life-threatening. These conduction system perturbations can manifest ...
BACKGROUND: Cardiologs® has developed the first electrocardiogram (ECG) algorithm that uses a deep neural network (DNN) for full 12‑lead ECG analysis, including rhythm, QRS and ST-T-U waves. We compared the accuracy of the first version of Cardiologs...
Journal of clinical monitoring and computing
Nov 11, 2018
The use of machine learning (ML) in healthcare has enormous potential for improving disease detection, clinical decision support, and workflow efficiencies. In this commentary, we review published and potential applications for the use of ML for moni...