학술논문
Validation of the myocardial-ischaemic-injury-index machine learning algorithm to guide the diagnosis of myocardial infarction in a heterogenous population: a prespecified exploratory analysis
Document Type
Article
Author
Mills, Nicholas L; Strachan, Fiona E; Tuck, Christopher; Shah, Anoop SV; Anand, Atul; Chapman, Andrew R; Ferry, Amy V; Lee, Kuan Ken; Doudesis, Dimitrios; Bularga, Anda; Wereski, Ryan; Taggart, Caelan; Lowry, Matthew TH; Mendusic, Filip; Kimenai, Dorien M; Sandeman, Dennis; Adamson, Philip D; Stables, Catherine L; Vallejos, Catalina A; Tsanas, Athanasios; Marshall, Lucy; Stewart, Stacey D; Fujisawa, Takeshi; Hautvast, Mischa; McPherson, Jean; McKinlay, Lynn; Ford, Ian; Newby, David E; Fox, Keith AA; Berry, Colin; Walker, Simon; Weir, Christopher J; Gray, Alasdair; Collinson, Paul O; Apple, Fred S; Reid, Alan; Cruikshank, Anne; Findlay, Iain; Amoils, Shannon; McAllister, David A; Maguire, Donogh; Stevens, Jennifer; Norrie, John; Andrews, Jack PM; Moss, Alastair; Anwar, Mohamed S; Hung, John; Malo, Jonathan; Fischbacher, Colin; Croal, Bernard L; Leslie, Stephen J; Keerie, Catriona; Parker, Richard A; Walker, Allan; Harkess, Ronnie; Wackett, Tony; Armstrong, Roma; Stirling, Laura; MacDonald, Claire; Sadat, Imran; Finlay, Frank; Charles, Heather; Linksted, Pamela; Young, Stephen; Alexander, Bill; Duncan, Chris; Yang, Jason; Shah, Anoop S V; Pickering, John W; Than, Martin P
Source
In The Lancet Digital Health May 2022 4(5):e300-e308
Subject
Language
ISSN
2589-7500