A Computer-Human Interaction Model to Improve the Diagnostic Accuracy and Clinical Decision-Making during 12-lead Electrocardiogram Interpretation
- Submitting institution
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University of Ulster
- Unit of assessment
- 12 - Engineering
- Output identifier
- 76399672
- Type
- D - Journal article
- DOI
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10.1016/j.jbi.2016.09.016
- Title of journal
- Journal of Biomedical Informatics
- Article number
- -
- First page
- 93
- Volume
- 64
- Issue
- -
- ISSN
- 1532-0464
- Open access status
- Compliant
- Month of publication
- September
- Year of publication
- 2016
- URL
-
-
- Supplementary information
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-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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8
- Research group(s)
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A - Healthcare Sensor Systems
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work brings significant novelty to the interpretation of 12-lead ECGs by replacing the conventional approach to decision support through providing incremental diagnostic suggestions designed to augment human expert decision. The work is built on significant novelty in the development of decision support systems and in the use of emerging interactive UX technologies. This work went on to underpin much of the ECG interpretation component of the 8m EU ECME Interreg programme and has resulted in two invited talks at the International Society for Computerised Electrocardiology annual Conference 2017 and 2020 (the latter being postponed until April 2021).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -