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An Annotation Driven Rule-based Algorithm for Suggesting Multiple 12-lead ECG Interpretations

Cairns, Andrew W., Bond, Raymond, Finlay, Dewar and Guldenring, Daniel (2017) An Annotation Driven Rule-based Algorithm for Suggesting Multiple 12-lead ECG Interpretations. In: Computing in Cardiology, Vancouver. IEEE. Vol 43 4 pp. [Conference contribution]

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URL: http://ieeexplore.ieee.org/document/7868702/

DOI: 10.22489/CinC.2016.1-4

Abstract

The 12-lead Electrocardiogram (ECG) is ubiquitously used as a diagnostic support tool to detect cardiovascular disease. However, it is difficult to read and is often incorrectly interpreted. This study aims to further previous research, which used of a set of interactive questions and prompts to guide an interpreter through the ECG reporting process. The model was named ‘Interactive Progressive based ECG Interpretation’ (IPI). In this study, the IPI model has been augmented with an automatic diagnoses suggestion tool following annotated analysis of an ECG. To accomplish this, a rule-based algorithm has been created to assess the interpreters’ ECG annotations to each of the interactive questions in the IPI model. This Differential Diagnoses Algorithm (DDA) was implemented using web technologies such as JavaScript and uses a modern device agnostic and language independent storage format (JSON) for defining the rules. Hence, by augmenting the IPI model with the DDA we hypothesize that this will further lower the number of interpretation errors and increase diagnostic accuracy in ECG interpretation.

Item Type:Conference contribution (Paper)
Keywords:ECG, electrocardiogram, clinical decision making, medical informatics, computer aided decision support, human computer interaction
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Faculty of Computing & Engineering > School of Engineering
Research Institutes and Groups:Engineering Research Institute
Engineering Research Institute > Nanotechnology & Integrated BioEngineering Centre (NIBEC)
Computer Science Research Institute > Smart Environments
Computer Science Research Institute
ID Code:37177
Deposited By: Dr Raymond Bond
Deposited On:16 Mar 2017 14:27
Last Modified:17 Oct 2017 16:28

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