Electrocardiographic prediction of arrhythmias
Information in electrocardiographic (ECG) signals is widely believed to have value in the short-term prediction of arrhythmias. This study evaluates the use of morphologic variability (MV), a recently proposed metric measuring subtle variability in the shape of ECG signals over long periods, to risk...
Main Authors: | Syed, Z., Scirica, B. M., Stultz, Collin M., Guttag, John V. |
---|---|
Other Authors: | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
Format: | Article |
Language: | en_US |
Published: |
Institute of Electrical and Electronics Engineers
2011
|
Online Access: | http://hdl.handle.net/1721.1/61700 https://orcid.org/0000-0002-3415-242X https://orcid.org/0000-0003-0992-0906 |
Similar Items
-
Automated beat-wise arrhythmia diagnosis using modified U-net on extended electrocardiographic recordings with heterogeneous arrhythmia types
by: Oh, Shu Lih, et al.
Published: (2020) -
Beatquency domain and machine learning improve prediction of cardiovascular death after acute coronary syndrome
by: Scirica, Benjamin M., et al.
Published: (2017) -
Motif Discovery in Physiological Datasets: A Methodology for Inferring Predictive Elements
by: Syed, Zeeshan, et al.
Published: (2012) -
Clustering and Symbolic Analysis of Cardiovascular Signals: Discovery and Visualization of Medically Relevant Patterns in Long-Term Data Using Limited Prior Knowledge
by: Syed, Zeeshan, et al.
Published: (2012) -
Learning to predict with supporting evidence: applications to clinical risk prediction
by: Raghu, Aniruddh, et al.
Published: (2022)