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

Andrew W. Cairns, Raymond Bond, Dewar Finlay, Daniel Guldenring

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.
LanguageEnglish
Title of host publicationUnknown Host Publication
Pages1-4
Number of pages4
Volume43
Publication statusE-pub ahead of print - 2 Mar 2017
EventComputing in Cardiology - Vancouver
Duration: 2 Mar 2017 → …

Conference

ConferenceComputing in Cardiology
Period2/03/17 → …

Fingerprint

Electrocardiography
Lead

Keywords

  • ECG
  • electrocardiogram
  • clinical decision making
  • medical informatics
  • computer aided decision support
  • human computer interaction

Cite this

Cairns, A. W., Bond, R., Finlay, D., & Guldenring, D. (2017). An Annotation Driven Rule-based Algorithm for Suggesting Multiple 12-lead ECG Interpretations. In Unknown Host Publication (Vol. 43, pp. 1-4)
Cairns, Andrew W. ; Bond, Raymond ; Finlay, Dewar ; Guldenring, Daniel. / An Annotation Driven Rule-based Algorithm for Suggesting Multiple 12-lead ECG Interpretations. Unknown Host Publication. Vol. 43 2017. pp. 1-4
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title = "An Annotation Driven Rule-based Algorithm for Suggesting Multiple 12-lead ECG Interpretations",
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.",
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Cairns, AW, Bond, R, Finlay, D & Guldenring, D 2017, An Annotation Driven Rule-based Algorithm for Suggesting Multiple 12-lead ECG Interpretations. in Unknown Host Publication. vol. 43, pp. 1-4, Computing in Cardiology, 2/03/17.

An Annotation Driven Rule-based Algorithm for Suggesting Multiple 12-lead ECG Interpretations. / Cairns, Andrew W.; Bond, Raymond; Finlay, Dewar; Guldenring, Daniel.

Unknown Host Publication. Vol. 43 2017. p. 1-4.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - 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.

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Cairns AW, Bond R, Finlay D, Guldenring D. An Annotation Driven Rule-based Algorithm for Suggesting Multiple 12-lead ECG Interpretations. In Unknown Host Publication. Vol. 43. 2017. p. 1-4