Cardiovascular

Myocardial Infarction

Latest AI and machine learning research in myocardial infarction for healthcare professionals.

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Showing 1366-1386 of 7,963 articles
Pretraining Strategies and Scaling for ECG Foundation Models: A Systematic Study

Specialized foundation models are beginning to emerge in various medical subdomains, but pretraining...

An electrocardiogram-based machine learning model for distinguishing complete Kawasaki disease.

Kawasaki disease (KD) is a systemic vasculitis in young children, and early diagnosis remains challe...

Screening for Rheumatic Heart Disease in Asymptomatic Children using Machine Learning from Electrocardiograms

Early detection of Rheumatic Heart Disease (RHD) is essential in reducing its associated mortality a...

Enhancing AI-Based ECG Delineation with Deep Learning Denoising Techniques

Evaluating canine electrocardiograms (ECGs) is challenging due to noise that can obscure clinically ...

PEACE: Cross-modal Enhanced Pediatric-Adult ECG Alignment for Robust Pediatric Diagnosis

Automated pediatric electrocardiogram (ECG) diagnosis remains challenging because models trained pre...

Deep Learning-Based Segmentation of Peritoneal Cancer Index Regions from CT Imaging

Peritoneal metastases are currently assessed using diagnostic laparoscopy to determine Sugarbaker's ...

Validating the Clinical Utility of CineECG 3D Reconstructions through Cross-Modal Feature Attribution

Deep learning models for 12-lead electrocardiogram (ECG) analysis achieve high diagnostic performanc...

Artificial Intelligence for Cardiac Biomarkers After Myocardial Infarction: A Systematic Review and a Leakage-Aware Modeling Framework

Aims To systematically evaluate how artificial intelligence and machine-learning (AI/ML) methods are...

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 ...

Electrocardiogram-based deep learning enables scalable screening of transthyretin amyloid cardiomyopathy

Transthyretin amyloid cardiomyopathy (ATTR -CM) is a treatable but underrecognized cause of heart fa...

Beyond Patient Invariance: Learning Cardiac Dynamics via Action-Conditioned JEPAs

Self-supervised learning in healthcare has largely relied on invariance-based objectives, which maxi...

Dissecting clinical reasoning failures in frontier artificial intelligence using 10,000 synthetic cases

Background: Current medical large language model (LLM) evaluations largely rely on small collections...

PlankFormer: Robust Plankton Instance Segmentation via MAE-Pretrained Vision Transformers and Pseudo Community Image Generation

Plankton monitoring is essential for assessing aquatic ecosystems but is limited by the labor-intens...

Inflammatory Biomarkers & Interpretable ML for SAP Risk Stratification in AIS Patients Undergoing Bridging Therapy

Stroke-associated pneumonia (SAP) is a common, severe complication in acute ischemic stroke (AIS) pa...

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...

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...

Stress Estimation in Elderly Oncology Patients Using Visual Wearable Representations and Multi-Instance Learning

Psychological stress is clinically relevant in cardio-oncology, yet it is typically assessed only th...

Learning ECG Image Representations via Dual Physiological-Aware Alignments

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

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