AIMC Topic: Stroke Volume

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Deep Learning-Enabled Assessment of Right Ventricular Function Improves Prognostication After Transcatheter Edge-to-Edge Repair for Mitral Regurgitation.

Circulation. Cardiovascular imaging Jan 21, 2025
BACKGROUND: Right ventricular (RV) function has a well-established prognostic role in patients with severe mitral regurgitation (MR) undergoing transcatheter edge-to-edge repair (TEER) and is typically assessed using echocardiography-measured tricusp...
Aged, 80 and over Male Stroke Volume Echocardiography Severity of Illness Index Humans Prognosis Female Aged Cardiac Catheterization Ventricular Function, Right Deep Learning Predictive Value of Tests Registries Mitral Valve Mitral Valve Insufficiency
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Predicting mortality after transcatheter aortic valve replacement using AI-based fully automated left atrioventricular coupling index.

Journal of cardiovascular computed tomography Jan 9, 2025
BACKGROUND: This study aimed to determine whether artificial intelligence (AI)-based automated assessment of left atrioventricular coupling index (LACI) can provide incremental value above other traditional risk factors for predicting mortality among...
Automation Aged Aged, 80 and over Atrial Function, Left Humans Male Risk Assessment Computed Tomography Angiography Artificial Intelligence Ventricular Function, Left Severity of Illness Index Transcatheter Aortic Valve Replacement Stroke Volume Retrospective Studies Aortic Valve Time Factors Treatment Outcome Predictive Value of Tests Female Aortic Valve Stenosis Coronary Angiography Risk Factors Radiographic Image Interpretation, Computer-Assisted
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Deep learning model to identify and validate hypotension endotypes in surgical and critically ill patients.

British journal of anaesthesia Jan 8, 2025
BACKGROUND: Hypotension is associated with organ injury and death in surgical and critically ill patients. In clinical practice, treating hypotension remains challenging because it can be caused by various underlying haemodynamic alterations. We aime...
Humans Stroke Volume Middle Aged Deep Learning Hypotension Heart Rate Algorithms Critical Illness Female Aged Male
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ECGEFNet: A two-branch deep learning model for calculating left ventricular ejection fraction using electrocardiogram.

Artificial intelligence in medicine Jan 3, 2025
Left ventricular systolic dysfunction (LVSD) and its severity are correlated with the prognosis of cardiovascular diseases. Early detection and monitoring of LVSD are of utmost importance. Left ventricular ejection fraction (LVEF) is an essential ind...
Humans Ventricular Function, Left Stroke Volume Deep Learning Electrocardiography Signal Processing, Computer-Assisted Ventricular Dysfunction, Left
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Reliability of post-contrast deep learning-based highly accelerated cardiac cine MRI for the assessment of ventricular function.

Magnetic resonance imaging Dec 19, 2024
OBJECTIVE: The total examination time can be reduced if high-quality two-dimensional (2D) cine images can be collected post-contrast to minimize non-scanning time prior to late gadolinium-enhanced imaging. This study aimed to assess the equivalency o...
Middle Aged Deep Learning Image Processing, Computer-Assisted Contrast Media Reproducibility of Results Heart Aged Heart Ventricles Adult Image Interpretation, Computer-Assisted Male Magnetic Resonance Imaging, Cine Humans Stroke Volume Ventricular Function Female
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Machine learning for stroke in heart failure with reduced ejection fraction but without atrial fibrillation: A post-hoc analysis of the WARCEF trial.

European journal of clinical investigation Nov 18, 2024
BACKGROUND: The prediction of ischaemic stroke in patients with heart failure with reduced ejection fraction (HFrEF) but without atrial fibrillation (AF) remains challenging. Our aim was to evaluate the performance of machine learning (ML) in identif...
Area Under Curve Stroke Humans Stroke Volume Heart Failure Middle Aged Machine Learning Atrial Fibrillation Support Vector Machine Female Blood Urea Nitrogen Ischemic Stroke Aged Male
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Natural Language Processing to Adjudicate Heart Failure Hospitalizations in Global Clinical Trials.

Circulation. Heart failure Nov 16, 2024
BACKGROUND: Medical record review by a physician clinical events committee is the gold standard for identifying cardiovascular outcomes in clinical trials, but is labor-intensive and poorly reproducible. Automated outcome adjudication by artificial i...
Heart Failure Hospitalization Benzhydryl Compounds Humans Male Clinical Trials as Topic Artificial Intelligence Stroke Volume Sodium-Glucose Transporter 2 Inhibitors Electronic Health Records Natural Language Processing Female Glucosides Reproducibility of Results
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Development and validation of a machine learning model to predict the risk of readmission within one year in HFpEF patients: Short title: Prediction of HFpEF readmission.

International journal of medical informatics Nov 14, 2024
BACKGROUND: Heart failure with preserved ejection fraction (HFpEF) is associated with elevated rates of readmission and mortality. Accurate prediction of readmission risk is essential for optimizing healthcare resources and enhancing patient outcomes...
Risk Assessment Risk Factors Humans ROC Curve Aged Machine Learning Heart Failure Male Retrospective Studies Patient Readmission Stroke Volume Female Middle Aged
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Detection of Right and Left Ventricular Dysfunction in Pediatric Patients Using Artificial Intelligence-Enabled ECGs.

Journal of the American Heart Association Nov 4, 2024
BACKGROUND: Early detection of left and right ventricular systolic dysfunction (LVSD and RVSD respectively) in children can lead to intervention to reduce morbidity and death. Existing artificial intelligence algorithms can identify LVSD and RVSD in ...
Male Ventricular Function, Left Stroke Volume Echocardiography Infant Adolescent Child, Preschool Child Electrocardiography Humans Artificial Intelligence Algorithms Retrospective Studies Female Predictive Value of Tests Ventricular Dysfunction, Right Ventricular Dysfunction, Left Ventricular Function, Right
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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...
Ventricular Dysfunction, Left Global Longitudinal Strain Humans Artificial Intelligence Prognosis Female Aged Deep Learning ROC Curve Electrocardiography Heart Ventricles Heart Failure Male Ventricular Function, Left Stroke Volume Echocardiography Middle Aged
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