AIMC Topic: Echocardiography, Stress

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The use of artificial intelligence for predicting postinfarction myocardial viability in echocardiographic images.

Cardiology journal May 14, 2024
BACKGROUND: Evaluation of standard echocardiographic examination with artificial intelligence may help in the diagnosis of myocardial viability and function recovery after acute coronary syndrome.
Time Factors Follow-Up Studies Predictive Value of Tests Aged Male Middle Aged Acute Coronary Syndrome Echocardiography, Stress Magnetic Resonance Imaging, Cine Tissue Survival Humans Myocardium Neural Networks, Computer Percutaneous Coronary Intervention Artificial Intelligence Myocardial Infarction Female Reproducibility of Results
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Development of artificial intelligence-based slow-motion echocardiography and clinical usefulness for evaluating regional wall motion abnormalities.

The international journal of cardiovascular imaging Nov 8, 2023
The diagnostic accuracy of exercise stress echocardiography (ESE) for myocardial ischemia requires improvement, given that it currently depends on the physicians' experience and image quality. To address this issue, we aimed to develop artificial int...
Echocardiography, Stress Echocardiography Predictive Value of Tests Myocardial Ischemia Humans Artificial Intelligence
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Artificial intelligence in stress echocardiography.

Asian journal of surgery Oct 29, 2023
Humans Artificial Intelligence Algorithms Echocardiography, Stress
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Artificially Intelligent Interpretation of Stress Echocardiography: The Future Is Now.

JACC. Cardiovascular imaging Jan 12, 2022
Artificial Intelligence Forecasting Sensitivity and Specificity Humans Dobutamine Predictive Value of Tests Exercise Test Echocardiography, Stress
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Analysis of nonstandardized stress echocardiography sequences using multiview dimensionality reduction.

Medical image analysis Nov 6, 2019
Alternative stress echocardiography protocols such as handgrip exercise are potentially more favorable towards large-scale screening scenarios than those currently adopted in clinical practice. However, these are still underexplored because the maxim...
Echocardiography, Stress Adenine Nucleotide Translocator 1 Male Cardiovascular Diseases Case-Control Studies Hand Strength Discriminant Analysis Heart Rate Machine Learning Female Young Adult Humans
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Identifying Ventricular Arrhythmias and Their Predictors by Applying Machine Learning Methods to Electronic Health Records in Patients With Hypertrophic Cardiomyopathy (HCM-VAr-Risk Model).

The American journal of cardiology Feb 27, 2019
Clinical risk stratification for sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HC) employs rules derived from American College of Cardiology Foundation/American Heart Association (ACCF/AHA) guidelines or the HCM Risk-SCD model (C-index ∼...
Humans Echocardiography, Stress Machine Learning Magnetic Resonance Imaging, Cine Prognosis Middle Aged Cardiomyopathy, Hypertrophic Predictive Value of Tests Risk Assessment Reproducibility of Results Retrospective Studies Tachycardia, Ventricular Electrocardiography Registries Risk Factors Electronic Health Records Male Female
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Artificial intelligence: a new clinical support tool for stress echocardiography.

Expert review of medical devices Jul 19, 2018
Decision Support Systems, Clinical Equipment and Supplies Echocardiography, Stress Humans Artificial Intelligence Machine Learning
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Stress Echocardiographic Evaluation for D-Transposition of the Great Arteries after Atrial Redirection: Unmasking Early Signs of Myocardial Dysfunction and Baffle Stenosis.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography Oct 26, 2016
BACKGROUND: The authors used semisupine cycle ergometry stress echocardiography to assess cardiac function and unmask baffle stenosis in patients with d-transposition of the great arteries after atrial redirection surgery.
Transposition of Great Vessels Ventricular Dysfunction Male Reproducibility of Results Humans Early Diagnosis Young Adult Treatment Outcome Retrospective Studies Echocardiography, Stress Sensitivity and Specificity Cardiac Surgical Procedures Superior Vena Cava Syndrome Female
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Machine Learning Analysis of Left Ventricular Function to Characterize Heart Failure With Preserved Ejection Fraction.

Circulation. Cardiovascular imaging Apr 1, 2018
BACKGROUND: Current diagnosis of heart failure with preserved ejection fraction (HFpEF) is suboptimal. We tested the hypothesis that comprehensive machine learning (ML) of left ventricular function at rest and exercise objectively captures difference...
Machine Learning Ventricular Dysfunction, Left Rest Algorithms Humans Aged Echocardiography, Stress Middle Aged Female Male Exercise Test Stroke Volume Heart Failure
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