Cardiovascular

Congestive Heart Failure

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

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Showing 757-777 of 3,389 articles
Leveraging Vision Transformers in Multimodal Models for Retinal OCT Analysis.

Optical Coherence Tomography (OCT) has become an indispensable imaging modality in ophthalmology, pr...

Hybrid Deep Learning for Survival Prediction in Brain Metastases Using Multimodal MRI and Clinical Data.

Survival prediction in patients with brain metastases remains a major clinical challenge, where tim...

Detection of Hypertrophic Cardiomyopathy on Electrocardiogram Using Artificial Intelligence.

BACKGROUND: Hypertrophic cardiomyopathy (HCM) is associated with significant morbidity and mortality...

An MRI-based deep transfer learning radiomics nomogram for predicting meningioma grade.

The aim of this study was to establish a nomogram based on clinical, radiomics, and deep transfer le...

Investigating the correlation between smoking and blood pressure via photoplethysmography.

Smoking has been widely identified for its detrimental effects on human health, particularly on the ...

Atrial Cardiomyopathy in Atrial Fibrillation: A Multimodal Diagnostic Framework.

Atrial fibrillation (AF) is increasingly recognized as the clinical manifestation of an underlying a...

The Accuracy of ChatGPT-4o in Interpreting Chest and Abdominal X-Ray Images.

Large language models (LLMs), such as ChatGPT, have emerged as potential clinical support tools to ...

Predicting the efficacy of bevacizumab on peritumoral edema based on imaging features and machine learning.

This study proposes a novel approach to predict the efficacy of bevacizumab (BEV) in treating peritu...

Expert consensus document on artificial intelligence of the Italian Society of Cardiology.

Artificial intelligence (AI), a branch of computer science focused on developing algorithms that rep...

Anatomy-derived 3D Aortic Hemodynamics Using Fluid Physics-informed Deep Learning.

Background Four-dimensional (4D) flow MRI provides assessment of thoracic aorta hemodynamic measures...

Machine Learning Assisted Stroke Prediction in Mechanical Circulatory Support: Predictive Role of Systemic Mitochondrial Dysfunction.

Stroke continues to be a major adverse event in advanced congestive heart failure (CHF) patients aft...

Deep Learning-based Aligned Strain from Cine Cardiac MRI for Detection of Fibrotic Myocardial Tissue in Patients with Duchenne Muscular Dystrophy.

Purpose To develop a deep learning (DL) model that derives aligned strain values from cine (noncontr...

Artificial Intelligence-Guided Lung Ultrasound by Nonexperts.

IMPORTANCE: Lung ultrasound (LUS) aids in the diagnosis of patients with dyspnea, including those wi...

Artificial intelligence-guided detection of under-recognised cardiomyopathies on point-of-care cardiac ultrasonography: a multicentre study.

BACKGROUND: Point-of-care ultrasonography (POCUS) enables cardiac imaging at the bedside and in comm...

Predictive Value of Machine Learning Models for Cerebral Edema Risk in Stroke Patients: A Meta-Analysis.

INTRODUCTION: Stroke patients are at high risk of developing cerebral edema, which can have severe c...

Estimation of Central Aortic Pressure Waveforms by Combination of a Meta-Learning Neural Network and a Physics-Driven Method.

The accurate non-invasive detection and estimation of central aortic pressure waveforms (CAPW) are c...

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