Re-engineering the clinical approach to suspected cardiac chest pain assessment in the emergency department by expediting research evidence to practice using artificial intelligence. (RAPIDx AI)—a cluster randomized study design

Authors

Ehsan Khan (ORCID: https://orcid.org/0000-0002-4544-4559)
Jonathan D. Karnon (ORCID: https://orcid.org/0000-0003-3220-2099)
Anton van den Hengel (ORCID: https://orcid.org/0000-0003-3027-8364)
Stephen Quinn (ORCID: https://orcid.org/0000-0002-1306-9686)
Johan Verjans (ORCID: https://orcid.org/0000-0002-8336-6774)
Derek P. Chew (ORCID: https://orcid.org/0000-0003-3593-296X)
Phil Tideman
Kristina Lambrakis (ORCID: https://orcid.org/0000-0002-6221-0244)
Louise Cullen (ORCID: https://orcid.org/0000-0001-6611-8229)
Tom Briffa
Cynthia Papendick (ORCID: https://orcid.org/0000-0002-1648-7672)

Institutions

Flinders University (AU)
University of South Australia (AU)
The University of Western Australia (AU)
Royal Brisbane and Women's Hospital (AU)
Government of Western Australia Department of Health (AU)
SA Health (AU)
Australian Centre for Robotic Vision (AU)
South Australian Health and Medical Research Institute (AU)
The University of Adelaide (AU)
Swinburne University of Technology (AU)

Publication Details

Journal: American Heart Journal
Published: 2025-02-22
DOI: https://doi.org/10.1016/j.ahj.2025.02.016
Citations: 2
Primary Topic: Cardiac Imaging and Diagnostics
Type: article
Field-Weighted Citation Impact: 2.72

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article

Re-engineering the clinical approach to suspected cardiac chest pain assessment in the emergency department by expediting research evidence to practice using artificial intelligence. (RAPIDx AI)—a cluster randomized study design

Ehsan Khan, Jonathan D. Karnon, Anton van den Hengel, Stephen Quinn et al.

Feb 22, 2025

2 citations

American Heart Journal

Cardiac Imaging and Diagnostics

2.72

article

Re-engineering the clinical approach to suspected cardiac chest pain assessment in the emergency department by expediting research evidence to practice using artificial intelligence. (RAPIDx AI)—a cluster randomized study design

Ehsan Khan, Jonathan D. Karnon, Anton van den Hengel, Stephen Quinn, Johan Verjans, Derek P. Chew, Phil Tideman, Kristina Lambrakis, Louise Cullen, Tom Briffa, Cynthia Papendick

February 22, 2025article en

2 citations

Abstract

No abstract available for this paper.

American Heart JournalVol. 285

Flinders University (AU), University of South Australia (AU), The University of Western Australia (AU), Royal Brisbane and Women's Hospital (AU), Government of Western Australia Department of Health (AU), SA Health (AU), Australian Centre for Robotic Vision (AU), South Australian Health and Medical Research Institute (AU), The University of Adelaide (AU), Swinburne University of Technology (AU)

Good health and well-being

Openalex Percentile: Top 12%

Cardiac Imaging and Diagnostics

2.72

DOI Open Access PDF OpenAlex

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Re-engineering the clinical approach to suspected cardiac chest pain assessment in the emergency department by expediting research evidence to practice using artificial intelligence. (RAPIDx AI)—a cluster randomized study design — Ehsan Khan, Jonathan D. Karnon, et al. · American Heart Journal (2025) | TGRS Research Map | TGRS