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References from Artificial intelligence-enhanced electrocardiography improves the detection of coronary artery disease. Local targets link to admitted publications; unresolved targets remain external evidence.
10.1056/nejmoa1901183
10.1056/nejmoa1901183 · External reference
Artificial intelligence-enabled ECG algorithm to identify patients with left ventricular systolic dysfunction presenting to the emergency department with dyspnea
10.1161/circep.120.008437 · 2020 · External reference
Screening for cardiac contractile dysfunction using an artificial intelligence-enabled electrocardiogram
10.1038/s41591-018-0240-2 · 2019 · External reference
Electrocardiogram screening for aortic valve stenosis using artificial intelligence
10.1093/eurheartj/ehab153 · 2021 · External reference
Development and validation of a deep-learning model to screen for hyperkalemia from the electrocardiogram
10.1001/jamacardio.2019.0640 · 2019 · External reference
Noninvasive assessment of dofetilide plasma concentration using a deep learning (neural network) analysis of the surface electrocardiogram: A proof of concept study
10.1371/journal.pone.0201059 · 2018 · External reference
Artificial intelligence-enhanced electrocardiography in cardiovascular disease management
10.1038/s41569-020-00503-2 · 2021 · External reference
Normal ECG in Patients With Severe Coronary Artery Disease
10.1001/jama.1997.03540360024011 · 1997 · External reference
Isolated significant left main coronary artery stenosis: angiographic, hemodynamic, and clinical findings in 16 patients
10.1016/0002-8703(91)90570-8 · 1991 · External reference
Exercise tomographic thallium-201 imaging in patients with severe coronary artery disease and normal electrocardiograms
10.7326/0003-4819-121-11-199412010-00001 · 1994 · External reference
The value of routine preoperative electrocardiography in predicting myocardial infarction after noncardiac surgery
10.1097/01.sla.0000261737.62514.63 · 2007 · External reference
Accelerated diagnostic protocol using high-sensitivity cardiac troponin T in acute chest pain patients
10.1016/j.ijcard.2015.02.006 · 2015 · External reference
Artificial intelligence-augmented ECG assessment: The promise and the challenge
10.1111/jce.13891 · 2019 · External reference
External validation of a deep learning electrocardiogram algorithm to detect ventricular dysfunction
10.1016/j.ijcard.2020.12.065 · 2021 · External reference
Artificial Intelligence ECG to Detect Left Ventricular Dysfunction in COVID-19: A Case Series
10.1016/j.mayocp.2020.09.020 · 2020 · External reference
Prospective validation of a deep learning electrocardiogram algorithm for the detection of left ventricular systolic dysfunction
10.1111/jce.13889 · 2019 · External reference
An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction
10.1016/s0140-6736(19)31721-0 · 2019 · External reference
An artificial intelligence-enabled ECG algorithm for the prediction and localization of angiography-proven coronary artery disease
10.3390/biomedicines10020394 · 2022 · External reference
Age and sex estimation using artificial intelligence from standard 12-Lead ECGs
10.1161/circep.119.007284 · 2019 · External reference
The influence of age and sex on the electrocardiogram
10.1007/978-3-319-77932-4_6 · 2018 · External reference
Sex differences in the ECG interpretation: a functional data analysis perspective
10.1109/rtsi50628.2021.9597363 · 2021 · External reference
QT/RR curvatures in healthy subjects: sex differences and covariates
10.1152/ajpheart.00577.2013 · 2013 · External reference
Modeling the recommended age for initiating coronary artery calcium testing among at-risk young adults
10.1016/j.jacc.2021.08.019 · 2021 · External reference
Sexual differences in genetic predisposition of coronary artery disease
10.1161/circgen.120.003147 · 2021 · External reference
Myocardial perfusion scintigraphy: the evidence
10.1007/s00259-003-1344-5 · 2004 · External reference
10.1016/j.jacc.2021.11.066
10.1016/j.jacc.2021.11.066 · External reference
Sexual dimorphism in the electrocardiographic dynamics of human ventricular repolarization
10.1161/hc2601.091738 · 2001 · External reference
Clinical and angiographic correlates of exercise-induced ST-segment elevation. Increased detection with multiple ECG leads
10.1161/01.cir.61.2.286 · 1980 · External reference
A new ST-segment elevation myocardial infarction equivalent pattern? Prominent T wave and J-point depression in the precordial leads associated with ST-segment elevation in lead aVr
10.1016/j.ajem.2013.09.037 · 2014 · External reference
Giant R wave, convex ST-segment elevation, and negative T wave during exercise treadmill test
10.1016/j.jelectrocard.2004.04.005 · 2004 · External reference
10.1111/j.1540-8167.1994.tb01184.x
10.1111/j.1540-8167.1994.tb01184.x · External reference
Hibernating myocardium: pathophysiology, diagnosis, and treatmentThis article is one of a selection of papers from the NATO Advanced Research Workshop on Translational Knowledge for Heart Health (published in part 2 of a 2-part Special Issue)
10.1139/y09-011 · 2009 · External reference
10.1093/jamiaopen/ooaf122
10.1093/jamiaopen/ooaf122 · External reference
xSiGra: explainable model for single-cell spatial data elucidation
10.1093/bib/bbae388 · 2024 · External reference
