Cardiovascular

Arrhythmias

Latest AI and machine learning research in arrhythmias for healthcare professionals.

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Non-Invasive Arterial Blood Pressure Waveform Generation in Critically Ill Patients: A Sensor-Based Deep Learning Approach

Continuous monitoring of Arterial Blood Pressure (ABP) in critically ill patients requires invasive ...

Empirical Ablation and Ensemble Optimization of a Convolutional Neural Network for CIFAR-10 Classification

Convolutional neural networks (CNNs) remain a central approach in image classification, but their pe...

Beyond Model Design: Data-Centric Training and Self-Ensemble for Gaussian Color Image Denoising

This paper presents our solution to the NTIRE 2026 Image Denoising Challenge (Gaussian color image d...

CARE-ECG: Causal Agent-based Reasoning for Explainable and Counterfactual ECG Interpretation

Large language models (LLMs) enable waveform-to-text ECG interpretation and interactive clinical que...

SiMing-Bench: Evaluating Procedural Correctness from Continuous Interactions in Clinical Skill Videos

Current video benchmarks for multimodal large language models (MLLMs) focus on event recognition, te...

Frailty Estimation in Elderly Oncology Patients Using Multimodal Wearable Data and Multi-Instance Learning

Frailty and functional decline strongly influence treatment tolerance and outcomes in older patients...

Learning ECG Image Representations via Dual Physiological-Aware Alignments

Electrocardiograms (ECGs) are among the most widely used diagnostic tools for cardiovascular disease...

Measuring the Unmeasurable: A Diagnostic Sensor for AI Reasoning Pathology in Sequential Clinical Decision-Making

Large Language Models achieve impressive accuracy on medical benchmarks that present clinical inform...

Bit-Identical Medical Deep Learning via Structured Orthogonal Initialization

Deep learning training is non-deterministic: identical code with different random seeds produces mod...

Detecting low left ventricular ejection fraction from ECG using an interpretable and scalable predictor-driven framework

Low left ventricular ejection fraction (LEF) frequently remains undetected until progression to symp...

Foundation Model for Cardiac Time Series via Masked Latent Attention

Electrocardiograms (ECGs) are among the most widely available clinical signals and play a central ro...

Performance Assessment of ECG Delineators on Single-Lead Wearable Ambulatory Data

Reliable interpretation of electrocardiograms (ECGs) requires precise identification of P, QRS, and ...

AI-Derived ECG Age Gap as a Digital Biomarker for Cardiovascular Risk Stratification

Cardiovascular diseases remain the leading cause of global mortality, and early risk stratification ...

The Alignment Tax: Response Homogenization in Aligned LLMs and Its Implications for Uncertainty Estimation

RLHF-aligned language models exhibit response homogenization: on TruthfulQA (n=790), 40-79% of quest...

Demographic-Aware Self-Supervised Anomaly Detection Pretraining for Equitable Rare Cardiac Diagnosis

Rare cardiac anomalies are difficult to detect from electrocardiograms (ECGs) due to their long-tail...

Holter-to-Sleep: AI-Enabled Repurposing of Single-Lead ECG for Sleep Phenotyping

Sleep disturbances are tightly linked to cardiovascular risk, yet polysomnography (PSG)-the clinical...

CARDIAC-FM: A Multimodal Foundation Model for Cardiovascular Risk Prediction Using ECG and Cardiac MRI

Atrial fibrillation and heart failure impose substantial health burdens worldwide, yet existing pred...

Pathology-Aware Multi-View Contrastive Learning for Patient-Independent ECG Reconstruction

Reconstructing a 12-lead electrocardiogram (ECG) from a reduced lead set is an ill-posed inverse pro...

Ablation Study of a Fairness Auditing Agentic System for Bias Mitigation in Early-Onset Colorectal Cancer Detection

Artificial intelligence (AI) is increasingly used in clinical settings, yet limited oversight and do...

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