AIMC Topic: 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 Humans Ventricular Dysfunction, Left Prognosis Heart Failure Artificial Intelligence ROC Curve Electrocardiography Deep Learning Stroke Volume Ventricular Function, Left Middle Aged Female Echocardiography Aged Male
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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.
Consensus Myocardial Contraction Predictive Value of Tests United Kingdom Echocardiography Neural Networks, Computer Global Longitudinal Strain Image Interpretation, Computer-Assisted Reproducibility of Results Datasets as Topic Humans Ventricular Dysfunction, Left Observer Variation Machine Learning Ventricular Function, Left Biomechanical Phenomena
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