Cardiovascular

Congestive Heart Failure

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

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Showing 1219-1239 of 3,596 articles
Assessment of HeartModelĀ® Automated Left Ventricular Ejection Fraction for Patients with Hypertrophic Cardiomyopathy

Cardiac myosin inhibitors (CMIs) have revolutionized care for patients with obstructive hypertrophic...

A Zero-Burden Sleep Foundation Model Built on Cardiorespiratory Signals from 800,000+ Hours of Multi-Ethnic Sleep Recordings

Sleep disorders pose a major global health burden and are associated with a wide range of adverse he...

Reliability of Artificial Intelligence-enhanced Electrocardiography

The scientific literature on artificial intelligence-enabled electrocardiography (AI-ECG) has define...

Artificial Intelligence-Enhanced Electrocardiogram Models for Detection of Left Ventricular Dysfunction: A Comparison Study

Several artificial intelligence-enhanced electrocardiogram (AI-ECG) models have shown promise in det...

Artificial intelligence-driven ECG biomarkers for screening of large pericardial effusion

Pericardial effusion can progress to life-threatening cardiac tamponade when large or rapidly accumu...

Machine Learning Prediction of Blood Pressure Control in Patients With Hypertension and Heart Failure Using Longitudinal Clinical Data

To develop and validate machine learning models for predicting Blood Pressure (BP) control status us...

Early Detection of Cardiovascular Disease Risk Using Multi-Parameter Biomarker Analysis and Machine Learning: A Prospective Cohort Study

Cardiovascular disease (CVD) remains the leading cause of mortality globally, with many events occur...

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...

Jan 2025 39764747
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...

Jan 2025 39778917
Flex-PE: Flexible and SIMD Multi-Precision Processing Element for AI Workloads

The rapid adaptation of data driven AI models, such as deep learning inference, training, Vision T...

MVQ:Towards Efficient DNN Compression and Acceleration with Masked Vector Quantization

Vector quantization(VQ) is a hardware-friendly DNN compression method that can reduce the storage ...

Multi-Stage Segmentation and Cascade Classification Methods for Improving Cardiac MRI Analysis

The segmentation and classification of cardiac magnetic resonance imaging are critical for diagnos...

Multi-Omics Integration With Machine Learning Identified Early Diabetic Retinopathy, Diabetic Macula Edema and Anti-VEGF Treatment Response.

PURPOSE: Identify optimal metabolic features and pathways across diabetic retinopathy (DR) stages, d...

Dec 2024 39671223
Graph Neural Networks for Quantifying Compatibility Mechanisms in Traditional Chinese Medicine

Traditional Chinese Medicine (TCM) involves complex compatibility mechanisms characterized by mult...

Elucidating the cellular determinants of the end-systolic pressure-volume relationship of the heart via computational modelling

The left ventricular end-systolic pressure-volume relationship (ESPVr) is a key indicator of cardi...

TATAA: Programmable Mixed-Precision Transformer Acceleration with a Transformable Arithmetic Architecture

Modern transformer-based deep neural networks present unique technical challenges for effective ac...

Electromechanical Dynamics of the Heart: A Study of Cardiac Hysteresis During Physical Stress Test

Cardiovascular diseases are best diagnosed using multiple modalities that assess both the heart's ...

MoRE: Multi-Modal Contrastive Pre-training with Transformers on X-Rays, ECGs, and Diagnostic Report

In this paper, we introduce a novel Multi-Modal Contrastive Pre-training Framework that synergisti...

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