Global Longitudinal Strain

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Artificial intelligence-assisted left ventricular global longitudinal strain assessment in patients with acute myocardial infarction: a RESUS-AMI trial sub-analysis.

The international journal of cardiovascular imaging Apr 29, 2025
PURPOSE: The aim of this sub-analysis of the RESUS-AMI trial was to evaluate the correlation of artificial intelligence (AI)-assisted echocardiographic global longitudinal strain (GLS) assessments with infarct size, left ventricular ejection fraction...
Humans Artificial Intelligence Aged Male Reproducibility of Results Female Percutaneous Coronary Intervention Image Interpretation, Computer-Assisted ST Elevation Myocardial Infarction Myocardial Contraction Global Longitudinal Strain Magnetic Resonance Imaging, Cine Observer Variation Middle Aged Predictive Value of Tests Treatment Outcome Stroke Volume Echocardiography Ventricular Function, Left
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AI derived ECG global longitudinal strain compared to echocardiographic measurements.

Scientific reports Nov 2, 2024
Left ventricular (LV) global longitudinal strain (LVGLS) is versatile; however, it is difficult to obtain. We evaluated the potential of an artificial intelligence (AI)-generated electrocardiography score for LVGLS estimation (ECG-GLS score) to diagn...
Global Longitudinal Strain Heart Ventricles Ventricular Dysfunction, Left Heart Failure Humans ROC Curve Electrocardiography Prognosis Deep Learning Artificial Intelligence Stroke Volume Female Ventricular Function, Left Aged Middle Aged Male Echocardiography
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2-Dimensional Echocardiographic Global Longitudinal Strain With Artificial Intelligence Using Open Data From a UK-Wide Collaborative.

JACC. Cardiovascular imaging Jul 10, 2024
BACKGROUND: Global longitudinal strain (GLS) is reported to be more reproducible and prognostic than ejection fraction. Automated, transparent methods may increase trust and uptake.
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Myocardial Contraction Consensus Global Longitudinal Strain Predictive Value of Tests United Kingdom Datasets as Topic Echocardiography Reproducibility of Results Observer Variation Image Interpretation, Computer-Assisted Ventricular Dysfunction, Left Ventricular Function, Left Neural Networks, Computer Humans Machine Learning Biomechanical Phenomena
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