A new algorithm to diagnose atrial ectopic origin from multi lead ECG systems - insights from 3D virtual human atria and torso
- Submitting institution
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The University of Hull
- Unit of assessment
- 12 - Engineering
- Output identifier
- 1397780
- Type
- D - Journal article
- DOI
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10.1371/journal.pcbi.1004026
- Title of journal
- PLoS computational biology
- Article number
- e1004026
- First page
- -
- Volume
- 11
- Issue
- 1
- ISSN
- 1553-734X
- Open access status
- Out of scope for open access requirements
- Month of publication
- January
- Year of publication
- 2015
- URL
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- Supplementary information
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- Request cross-referral to
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- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
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- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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7
- Research group(s)
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- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Atrial fibrillation affects over 33 million people worldwide. Routine treatment identifies sites responsible for abnormal electrical activity by highly invasive electrophysiological studies. These take several hours with X-ray guidance, exposing patients and clinicians to risk. Using the most detailed biophysical computer model to date, this study shows how these sites can be determined non-invasively by electrocardiography with success rates up to 93%, the best achieved with such models. The research was reported in national and international news outlets e.g. https://www.sciencedaily.com/releases/2015/01/150108141411.htm; https://www.manchestereveningnews.co.uk/news/greater-manchester-news/thousands-lives-could-saved-new-8557207. It led to a personal invitation for Langley to join the International Consortium for ECG Imaging https://www.ecg-imaging.org/workgroups/atrial-arrhythmia
- Author contribution statement
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- Non-English
- No
- English abstract
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