Myocardial Infarction

A Deformable Lead-Attention Fusion Network for Multi-Label ECG Classification Integrating Clinical Metadata.

Cardiovascular diseases remain a major global health burden, making accurate elec-trocardiogram (ECG) analysis essential for timely diagnosis. While deep learning-based methods have made significant progress in automating ECG classification, they are often limited by the variability of ECG signals, the frequent presence of multiple cardiac abnor-malities, and the inadequate integration of diverse ...

The Imaging Compass: Navigating Reperfusion in Acute Ischemic Stroke.

The management of acute ischemic stroke has shifted from rigid time-based protocols to imaging-driven, tissue-based reperfusion strategies. Non-contrast CT and CT angiography remain the indispensable frontline for rapid triage, particularly in community and low-resource settings. However, magnetic resonance imaging (MRI) provides unique biological information that complements CT-based assessment: ...

Predictive, preventive, and personalized medicine in statin-treated patients with NSTE-ACS, HFpEF, and type 2 diabetes: a data-driven model for long-term residual risk assessment.

BACKGROUND: Despite significant advances in guideline-directed medical therapy (GDMT), statin-treated patients with non-ST-elevation acute coronary sy...

Reducing Racial Disparities in Stroke Thrombolysis Using Fairness-Aware Machine Learning.

Racial and ethnic disparities in the administration of intravenous thrombolysis (IVT) for acute ischemic stroke (AIS) remain persistent, raising conce...

ECG-ARD: Autoregressive ECG Denoising With Dual-Domain Fusion and a Vector-Quantized Bottleneck.

Electrocardiogram (ECG) recordings are frequently corrupted by nonstationary artifacts such as baseline wander, muscle activity, and electrode motion,...

A ciliated intravascular soft millirobot for multimodal in-flow collective manipulation.

The laminar nature of blood flow and the resulting boundary layer pose substantial challenges for transverse mass transport in blood vessels, limiting...

Patient Stratification for Improving Acute Chest Pain Management and Mitigating Emergency Department Crowding: Machine Learning Model Development and Validation.

BACKGROUND: Acute chest pain (ACP) is one of the most common chief complaints in the emergency department (ED), accounting for approximately 8% of all...

High-resolution modeling of indoor radon exposure with uncertainty quantification in Utah.

Indoor radon accounts for 37% of population-level exposure to ionizing radiation in the United States. However, radon metrics are typically reported a...

Validation of an Artificial Intelligence-Derived ECG Algorithm for Detecting Cardiac Amyloidosis in Patients With Heart Failure With Preserved Ejection Fraction: Clinical Application and Prognostic Implications.

BACKGROUND: Cardiac transthyretin amyloidosis (ATTR-CA) is frequently underdiagnosed and commonly presents as heart failure with preserved ejection fr...

Prediction of Atrial Fibrillation Occurrence With Handheld Mobile Electrocardiogram: Deep Learning Model Development Using Real-World Data.

BACKGROUND: Atrial fibrillation (AF) is a common arrhythmia associated with an increased risk of stroke and heart failure. To improve prevention, rece...

Coronary Artery Calcification: Contemporary Diagnosis from Invasive Imaging to Percutaneous Treatment.

Coronary artery calcification (CAC) represents a significant challenge in contemporary interventional cardiology, substantially affecting percutaneous...

Updates on Imaging Modalities for the Diagnosis of Aortic Stenosis.

Aortic stenosis (AS) is the most common degenerative valvular disease in elderly patients and is linked to high morbidity and mortality. Accurate diag...

Evaluation of HRV-PRV agreement with autoencoder-based signal quality assessment in resting and dynamic conditions.

Objective.Pulse-to-pulse intervals obtained from continuous non-invasive blood pressure (CNBP) signals can be used to derive pulse rate variability (P...

Left Atrial Stiffness Index for Refining Diastolic Stress Test Selection in Suspected Heart Failure With Preserved Ejection Fraction.

INTRODUCTION: Diagnosing heart failure with preserved ejection fraction (HFpEF) remains challenging in patients with exertional dyspnea and inconclusi...

Artificial Intelligence Analysis of Standard 12-Lead Electrocardiograms for Screening of Symptomatic Diabetic Peripheral Neuropathy.

AIM: To investigate whether artificial intelligence (AI) models trained on standard 12-lead electrocardiograms (ECG) can identify symptom-defined diab...

AI-ECG Detection of Structural Heart Disease in the Community Setting: Transportability and Spectrum Effects in the PREVUE-VALVE Study.

BACKGROUND: Artificial intelligence (AI) diagnostic models are typically developed in hospital-based populations enriched for disease prevalence and s...

HRV-anchored autonomic-morphological structured factorization for interpretable multimodal cardiovascular risk prediction.

Cardiovascular risk prediction from heterogeneous physiological signals supports early warning in bedside and wearable monitoring, where ECG, PPG, HRV...

Federated learning for MRI-based BrainAGE: A multicenter study on post-stroke functional outcome prediction.

OBJECTIVE: Brain-predicted age difference (BrainAGE) is a neuroimaging biomarker reflecting brain health, with potential implications for post-stroke ...

The role of dataset integrity, calibration and signal quality in neural network-based blood pressure estimation.

Cuffless blood pressure (BP) estimation via photoplethysmography (PPG) and machine learning has been widely studied, yet reported accuracy remains bel...

BraMARS: An Interpretable Histopathology-Driven Deep Learning Model for Brain Metastasis Risk Stratification in Surgically Resected Limited-Stage SCLC.

Brain metastasis (BM) is a major cause of mortality in limited-stage small-cell lung cancer (LS-SCLC). Prophylactic cranial irradiation (PCI) reduces ...