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Automated QT analysis that learns from cardiologist annotations.

Abstract:

BACKGROUND: Reliable, automated QT analysis would allow the use of all the ECG data recorded during continuous Holter monitoring, rather than just intermittent 10-second ECGs. METHODS: BioQT is an automated ECG analysis system based on a Hidden Markov Model, which is trained to segment ECG signals using a database of thousands of annotated waveforms. Each sample of the ECG signal is encoded by its wavelet transform coefficients. BioQT also produces a confidence measure which can be used to i...

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Publication status:
Published

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Sub department:
Institute of Biomedical Engineering
Role:
Author
Journal:
Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc
Volume:
14 Suppl 1
Pages:
S9-21
Publication date:
2009-01-01
DOI:
EISSN:
1542-474X
ISSN:
1082-720X
Source identifiers:
61651
Language:
English
Keywords:
Pubs id:
pubs:61651
UUID:
uuid:df788457-4516-46c9-b86a-fc23d76f1ae9
Local pid:
pubs:61651
Deposit date:
2012-12-19

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