Cardiovascular

Congestive Heart Failure

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

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Showing 1345-1365 of 4,489 articles
A novel unsupervised machine learning strategy to handle multimodal cardiac PET/MRI data

Arrhythmogenic left ventricular cardiomyopathy is a genetic myocardial disease difficult to diagnose...

Unsupervised phenotype clustering of non-ischemic dilated cardiomyopathy with AI-assisted T1 mapping cardiac MR

Aims: Prognostic stratification and individual management are essential in the heterogeneous populat...

SURPASS-HF: Safety and Utility of Remote Pulmonary Artery Sensor Shared-management in Heart Failure

_ SURPASS-HF: Safety and Utility of Remote Pulmonary Artery Sensor Shared-management in Heart Failur...

Causal-RetiGraph: Cross-Cohort Retinal Support and Same-Subject Pathway Analysis for Diabetic Retinopathy

Diabetic retinopathy (DR) is a local retinal lesion process and a visible manifestation of systemic ...

Multi-task artificial intelligence annotation of echocardiographic images: a retrospective multi-cohort study

Summary Background A comprehensive transthoracic echocardiogram involves the assessment of over 70 p...

A Latent ODE Approach to Spatiotemporal Modeling of Cine Cardiac MRI

Cardiac magnetic resonance imaging (CMR) captures rich spatiotemporal information about ventricular ...

Development and Validation of Machine Learning Models for Predicting Initiation of Emergency Dialysis in Advanced Chronic Kidney Disease

BackgroundInitiation of emergency dialysis, often requiring temporary catheter owing to unprepared d...

Agentic Autodiscovery of Diastolic Dysfunction Phenotypes from Surface Electrocardiogram

Background: Left ventricular diastolic dysfunction (LVDD) is a major determinant of heart failure (H...

Multivariate Echocardiographic Phenotyping of Hypertensive Heart Failure Using Unsupervised Machine Learning: A Pilot Study

Background Heart failure in hypertensive patients is heterogeneous and poorly captured by traditiona...

Comparative Analysis of Machine Learning Models vs. Traditional Clinical Calculators for Cardiovascular Risk Prediction

Background: Cardiovascular diseases (CVD) remain the leading global cause of mortality, responsible ...

Fusion-E2Pulse: A Multimodal Event-RGB Fusion Network for Non-contact Pulse Wave Reconstruction

Non-contact pulse wave reconstruction hinges on the precise recovery of waveform morphology, includi...

Small molecule biomarkers predictive of Chagas disease progression

Chagas disease (CD), caused by the protozoan parasite Trypanosoma cruzi, affects an estimated 10.5 m...

BenDi: An Energy-Efficient Quasi-Stochastic Systolic Architecture for Edge Bioelectronics

Continuous long-term monitoring and diagnosis of biomedical signals, such as electrocardiograms (ECG...

DMT: Demographic Conditioning, Morphology-Enhanced Transformer for Cuffless Blood Pressure Estimation from PPG Signals

Blood pressure (BP) is a key marker for cardiovascular risk assessment and therapeutic decision-maki...

Patterns of Typical and Atypical Age-related Brainstem Volume losses

Background: The brainstem and its different sub-systems control essential functions such as motor ag...

Uncertainty Reliability Under Domain Shift: An Investigation for Data-Driven Blood Pressure Estimation in Photoplethysmography

Uncertainty quantification (UQ) is critical for safety-critical domains like healthcare, yet it is r...

Evo 2 Predicts Cardiomyopathy-Associated Variants and Elucidates Their Underlying Mechanisms

Background: Although advances in next-generation sequencing have accelerated the identification of g...

A CUBS-Compatible Ultrasound Morphology and Uncertainty-Aware Baseline for Carotid Intima-Media Segmentation and Preliminary Risk Prediction

Carotid atherosclerosis is a major contributor to ischemic stroke and transient ischemic attack. Con...

Predictive Radiomics for Evaluation of Cancer Immune SignaturE in Glioblastoma: the PRECISE-GBM study

Background: Radiogenomics allows identification of radiological biomarkers for genomic phenotypes. I...

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