Cardiovascular

Congestive Heart Failure

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

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Showing 1301-1320 of 5,063 articles

Exploring Deep Learning and Ultra-Widefield Imaging for Diabetic Retinopathy and Macular Edema

Diabetic retinopathy (DR) and diabetic macular edema (DME) are leading causes of preventable blindness among working-age adults. Traditional approaches in the literature focus on standard color fundus photography (CFP) for the detection of these conditions. Nevertheless, recent ultra-widefield imaging (UWF) offers a significantly wider field of view in comparison to CFP. Motivated by this, the pre...

Mar 9 2026 2603.08235v1

Echocardiography-Based, Artificial Intelligence-Enabled Electrocardiography (AI-ECG) for Diastolic Hemodynamics Phenotyping in Acute Heart Failure (AHF)

Background: Acute heart failure (AHF) exhibits marked heterogeneity in diastolic hemodynamics, yet comprehensive echocardiographic assessment of diastolic function (DF) and filling pressure (FP) is often infeasible. We evaluated whether artificial intelligence-enabled electrocardiography (AI-ECG) could provide scalable DF grading and FP estimation in hospitalized AHF patients. Methods: We retrospe...

DIA-PINN. A physics-informed machine learning method to estimate global intrinsic diastolic chamber properties of the left ventricle from pressure-volume data

Background: Pressure volume (PV) loop analysis remains the gold standard for assessing the intrinsic global diastolic properties of the left ventricle...

Development of a Multi-Trait Polygenic Score for Intrinsic Capacity

Background: Intrinsic capacity (IC) is a key marker of healthy ageing, which captures an individuals physical and mental capacities, measured across f...

Can Agents Distinguish Visually Hard-to-Separate Diseases in a Zero-Shot Setting? A Pilot Study

The rapid progress of multimodal large language models (MLLMs) has led to increasing interest in agent-based systems. While most prior work in medical...

Feb 26 2026 2602.22959v1
Bitwise Systolic Array Architecture for Runtime-Reconfigurable Multi-precision Quantized Multiplication on Hardware Accelerators

Neural network accelerators have been widely applied to edge devices for complex tasks like object tracking, image recognition, etc. Previous works ha...

Feb 26 2026 2602.23334v1
Reliable XAI Explanations in Sudden Cardiac Death Prediction for Chagas Cardiomyopathy

Sudden cardiac death (SCD) is unpredictable, and its prediction in Chagas cardiomyopathy (CC) remains a significant challenge, especially in patients ...

Feb 25 2026 2602.22288v1
Multimodal MRI Report Findings Supervised Brain Lesion Segmentation with Substructures

Report-supervised (RSuper) learning seeks to alleviate the need for dense tumor voxel labels with constraints derived from radiology reports (e.g., vo...

Feb 24 2026 2602.20994v1
AI-Detected Asymptomatic Atrial Fibrillation and Risk of Incident Ischemic Stroke and Cardiovascular Events: A UK Biobank Study

Background: Advances in wearable devices and machine-learning-based ECG analysis enable highly accurate detection of atrial fibrillation (AF) outside ...

RED RHD (Rice Early Detection for Rheumatic Heart Disease): AI-Based Adaptive Multi-Regional System for Early Detection and Murmur Classification of Rheumatic Heart Disease

This study presents RED RHD, a machine learning methodology for early detection and classification of Rheumatic Heart Disease (RHD) using heart sound ...

Multimodal Machine Learning Reveals the Genomic and Proteomic Architecture of Heart Failure with Preserved Ejection Fraction

Heart failure with preserved ejection fraction (HFpEF) affects over 30 million people and lacks disease-modifying therapies. Although genomic-led drug...

Addressing data annotation scarcity in Brain Tumor Segmentation on 3D MRI scan Using a Semi-Supervised Teacher-Student Framework

Accurate brain tumor segmentation from MRI is limited by expensive annotations and data heterogeneity across scanners and sites. We propose a semi-sup...

Feb 9 2026 2602.08797v1
Orientation-Robust Latent Motion Trajectory Learning for Annotation-free Cardiac Phase Detection in Fetal Echocardiography

Fetal echocardiography is essential for detecting congenital heart disease (CHD), facilitating pregnancy management, optimized delivery planning, and ...

Feb 6 2026 2602.06761v1
ESUS-AI:a machine learning framework to estimate the most likely embolic source in embolic stroke of undetermined source

Background and Purpose Embolic stroke of undetermined source (ESUS) emains a major diagnostic challenge in vascular neurology, as a substantial propor...

Personalised approach to hypertension treatment: Rationale and design of the HYPERMARKER randomised trial

Background and Objective: Blood pressure treatment response is variable in individual patients, and the choice of medical therapy is often dependent o...

Machine Learning Identifies Distinct Treg-Mediated Remodeling in HFpEF Hearts Treated with Neonatal Mesenchymal Stem Cells and Their Secretome

Background: Heart failure with preserved ejection fraction (HFpEF) remains a major therapeutic challenge due to its complex pathophysiology and pronou...

Machine Learning Ensemble Reveals Distinct Molecular Pathways of Retinal Damage in Spaceflown Mice

Spaceflight-associated neuro-ocular syndrome (SANS) threatens astronaut health during long-duration missions, yet its molecular pathology remains uncl...

Deep Learning Decodes Latent ECG Signatures of Stress Cardiomyopathy

Background Stress cardiomyopathy (SCM) shares features with acute myocardial infarction (AMI) which may lead to misdiagnosis and misaligned management...

Gene-exposure interactions regulate cytokine-mediated chronic inflammation and cardiac remodeling

Background: Chronic inflammation predicts adverse cardiovascular outcomes, but mechanisms linking systemic inflammation to cardiac remodeling remain i...

Artificial Intelligence-Enabled Echocardiographic Assessment of Right Ventricular Function

Background: Right ventricular (RV) function is an important predictor of morbidity and mortality in various cardiovascular conditions. Nevertheless, i...

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