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 Randomised Clinical Trial Design - 03/08/22
Doi : 10.1016/j.hlc.2022.06.373
E. Khan 1, 2, K. Lambrakis 1, 2, T. Briffa 3, L. Cullen 4, 5, 6, J. Karnon 2, C. Papendick 7, S. Quinn 8, P. Tideman 1, 2, A. Van Den Hengel 9, J. Verjans 9, 10, D. Chew 1, 2
1 Flinders Medical Centre, Bedford Park, SA, Australia
2 Flinders University, Adelaide, Australia
3 School of Population and Global Health, University of Western Australia, Perth, Australia
4 Emergency and Trauma Centre, Royal Brisbane and Women’s Hospital, Brisbane, Australia
5 School of Public Health, Queensland University of Technology, Brisbane, Australia
6 School of Medicine, University of Queensland, Brisbane, Australia
7 Royal Adelaide Hospital, Adelaide, Australia
8 Department of Statistics, Department of Health Science and Biostatistics, Swinburne University of Technology, Melbourne, Australia
9 Australian Institute for Machine Learning (AIML), The University of Adelaide, Adelaide, Australia
10 South Australian Health and Medical Research Institute, Adelaide, Australia
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© 2022
Publié par Elsevier Masson SAS.
Vol 31 - N° S3
P. S224-S225 - 2022 Retour au numéro
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