AI Medical Compendium Topic

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Diastole

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Cardiac phase detection in echocardiography using convolutional neural networks.

Scientific reports
Echocardiography is a commonly used and cost-effective test to assess heart conditions. During the test, cardiologists and technicians observe two cardiac phases-end-systolic (ES) and end-diastolic (ED)-which are critical for calculating heart chambe...

Automated echocardiographic left ventricular dimension assessment in dogs using artificial intelligence: Development and validation.

Journal of veterinary internal medicine
BACKGROUND: Artificial intelligence (AI) could improve accuracy and reproducibility of echocardiographic measurements in dogs.

Diastolic function assessment with four-dimensional flow cardiovascular magnetic resonance using automatic deep learning E/A ratio analysis.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Diastolic left ventricular (LV) dysfunction is a powerful contributor to the symptoms and prognosis of patients with heart failure. In patients with depressed LV systolic function, the E/A ratio, the ratio between the peak early (E) and t...

Reproducibility of artificial intelligence-enabled plaque measurements between systolic and diastolic phases from coronary computed tomography angiography.

European radiology
OBJECTIVES: Current coronary CT angiography (CTA) guidelines suggest both end-systolic and mid-diastolic phases of the cardiac cycle can be used for CTA image acquisition. However, whether differences in the phase of the cardiac cycle influence coron...

Tricuspid valve flow measurement using a deep learning framework for automated valve-tracking 2D phase contrast.

Magnetic resonance in medicine
PURPOSE: Tricuspid valve flow velocities are challenging to measure with cardiovascular MR, as the rapidly moving valvular plane prohibits direct flow evaluation, but they are vitally important to diastolic function evaluation. We developed an automa...

Automated echocardiographic diastolic function grading: A hybrid multi-task deep learning and machine learning approach.

International journal of cardiology
BACKGROUND: Assessing left ventricular diastolic function (LVDF) with echocardiography as per ASE guidelines is tedious and time-consuming. The study aims to develop a fully automatic approach of this procedure by a lightweight hybrid algorithm combi...

Deep learning method with integrated invertible wavelet scattering for improving the quality ofcardiac DTI.

Physics in medicine and biology
Respiratory motion, cardiac motion and inherently low signal-to-noise ratio (SNR) are major limitations ofcardiac diffusion tensor imaging (DTI). We propose a novel enhancement method that uses unsupervised learning based invertible wavelet scatterin...

Diagnostic accuracy of artificial intelligence for identifying systolic and diastolic cardiac dysfunction in the emergency department.

The American journal of emergency medicine
INTRODUCTION: Cardiac point-of-care ultrasound (POCUS) can evaluate for systolic and diastolic dysfunction to inform care in the Emergency Department (ED). However, accurate assessment can be limited by user experience. Artificial intelligence (AI) h...

Artificial Intelligence ECG Diastolic Dysfunction and Survival in Cardiac Intensive Care Unit Patients.

Journal of the American Heart Association
BACKGROUND: Left ventricular diastolic dysfunction (LVDD) predicts mortality in patients in cardiac intensive care units. An artificial intelligence enhanced ECG (AIECG) algorithm can predict LVDD and mortality in general populations but has not been...