Clinical decision support using machine learning and cardiac troponin for the diagnosis of myocardial infarction
Eur Heart J Acute Cardiovasc Care
.
2024 Aug 28;13(8):634-636.
doi: 10.1093/ehjacc/zuae085.
Authors
Martin P Than
1
,
John W Pickering
1
2
,
Johannes Mair
3
,
Nicholas L Mills
4
5
;
Study Group on Biomarkers of the Association for Acute CardioVascular Care of the ESC
Collaborators
Study Group on Biomarkers of the Association for Acute CardioVascular Care of the ESC
:
Bertil Lindahl
,
Jasper Boeddinghaus
,
Louise Cullen
,
Lori Daniels
,
Ola Hammarsten
,
Kurt Huber
,
Evangelos Giannitsis
,
Allan S Jaffe
,
Dorien M Kimenai
,
Konstantin A Krychtiuk
,
Martin Möckel
,
Christian Mueller
,
Matthias Thielmann
,
Kristian Thygesen
,
Johannes Mair
,
Nicholas L Mills
Affiliations
1
Emergency Department, Christchurch Hospital, Private Bag 4710, Christchurch 8140, New Zealand.
2
Christchurch Heart Institute, Department of Medicine, University of Otago, Christchurch, New Zealand.
3
Department of Internal Medicine III-Cardiology and Angiology, Innsbruck Medical University, Innsbruck, Austria.
4
BHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK.
5
Usher Institute, University of Edinburgh, Edinburgh, UK.
PMID:
39026425
DOI:
10.1093/ehjacc/zuae085
No abstract available
MeSH terms
Biomarkers* / blood
Decision Support Systems, Clinical*
Humans
Machine Learning*
Myocardial Infarction* / blood
Myocardial Infarction* / diagnosis
Troponin / blood
Substances
Biomarkers
Troponin