Cardiovascular

Congestive Heart Failure

Latest AI and machine learning research in congestive heart failure for healthcare professionals.

3,374 articles
Stay Ahead - Weekly Congestive Heart Failure research updates
Subscribe
Browse Specialties
Showing 148-168 of 3,374 articles
A Multicenter Evaluation of the Impact of Therapies on Deep Learning-Based Electrocardiographic Hypertrophic Cardiomyopathy Markers.

Artificial intelligence-enhanced electrocardiography (AI-ECG) can identify hypertrophic cardiomyopat...

Comprehensive prediction of outcomes in patients with ST elevation myocardial infarction (STEMI) using tree-based machine learning algorithms.

ST elevation myocardial infarction (STEMI), a subtype of acute coronary syndrome, is one of the lead...

Artificial intelligence modeling of biomarker-based physiological age: Impact on phase 1 drug-metabolizing enzyme phenotypes.

Age and aging are important predictors of health status, disease progression, drug kinetics, and eff...

Grade prediction of lesions in cerebral white matter using a convolutional neural network.

We established a diagnostic method for cerebral white matter lesions using MRI images and examined t...

Detection of Right and Left Ventricular Dysfunction in Pediatric Patients Using Artificial Intelligence-Enabled ECGs.

BACKGROUND: Early detection of left and right ventricular systolic dysfunction (LVSD and RVSD respec...

AI derived ECG global longitudinal strain compared to echocardiographic measurements.

Left ventricular (LV) global longitudinal strain (LVGLS) is versatile; however, it is difficult to o...

Detection of Macular Neovascularization in Eyes Presenting with Macular Edema using OCT Angiography and a Deep Learning Model.

PURPOSE: To test the diagnostic performance of an artificial intelligence algorithm for detecting an...

A machine learning tool for identifying newly diagnosed heart failure in individuals with known diabetes in primary care.

AIMS: We aimed to create a predictive model utilizing machine learning (ML) to identify new cases of...

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

INTRODUCTION: Cardiac point-of-care ultrasound (POCUS) can evaluate for systolic and diastolic dysfu...

Rapid estimation of left ventricular contractility with a physics-informed neural network inverse modeling approach.

Physics-based computer models based on numerical solutions of the governing equations generally cann...

Machine learning and radiomics for ventricular tachyarrhythmia prediction in hypertrophic cardiomyopathy: insights from an MRI-based analysis.

BACKGROUND: Myocardial fibrosis is often detected in patients with hypertrophic cardiomyopathy (HCM)...

Prediction model of in-hospital cardiac arrest using machine learning in the early phase of hospitalization.

In hospitals, the deterioration of a patient's condition leading to death is often preceded by physi...

Multi-modality artificial intelligence-based transthyretin amyloid cardiomyopathy detection in patients with severe aortic stenosis.

PURPOSE: Transthyretin amyloid cardiomyopathy (ATTR-CM) is a frequent concomitant condition in patie...

Deep Learning Model of Diastolic Dysfunction Risk Stratifies the Progression of Early-Stage Aortic Stenosis.

BACKGROUND: The development and progression of aortic stenosis (AS) from aortic valve (AV) sclerosis...

The value of CCTA combined with machine learning for predicting angina pectoris in the anomalous origin of the right coronary artery.

BACKGROUND: Anomalous origin of coronary artery is a common coronary artery anatomy anomaly. The ano...

Browse Specialties