Cardiovascular

Myocardial Infarction

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

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Showing 1408-1428 of 7,963 articles
Detecting Structural Heart Disease from Electrocardiograms via a Generalized Additive Model of Interpretable Foundation-Model Predictors

Structural heart disease (SHD) is a prevalent condition with many undiagnosed cases, and early detec...

Chain of Flow: A Foundational Generative Framework for ECG-to-4D Cardiac Digital Twins

A clinically actionable Cardiac Digital Twin (CDT) should reconstruct individualised cardiac anatomy...

RhythmBERT: A Self-Supervised Language Model Based on Latent Representations of ECG Waveforms for Heart Disease Detection

Electrocardiogram (ECG) analysis is crucial for diagnosing heart disease, but most self-supervised l...

Learning geometry-dependent lead-field operators for forward ECG modeling

Modern forward electrocardiogram (ECG) computational models rely on an accurate representation of th...

A Framework for Cross-Domain Generalization in Coronary Artery Calcium Scoring Across Gated and Non-Gated Computed Tomography

Coronary artery calcium (CAC) scoring is a key predictor of cardiovascular risk, but it relies on EC...

Multimodal Deep Learning for Structural Heart Disease Prediction from ECG and Clinical Data

This research presents multimodal deep learning for structural heart disease prediction. We evaluate...

Prompting is All You Need: How to Make LLMs More Helpful for Clinical Decision Support

Importance: Large language models (LLMs) offer potential decision support, but their accuracy varies...

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 accur...

Agentic Trial Emulation to Learn Health System-specific Drug Effects At Scale

Objective: Electronic Health Record (EHR)-based trial emulation can support translation of randomize...

Position: Evaluation of ECG Representations Must Be Fixed

This position paper argues that current benchmarking practice in 12-lead ECG representation learning...

Wavelet-Domain Multi-Representation and Ensemble Learning for Automated ECG Analysis

Accurate diagnosis of cardiac abnormalities from electrocardiogram signals remains a central challen...

CAMEL: An ECG Language Model for Forecasting Cardiac Events

Electrocardiograms (ECG) are electrical recordings of the heart that are critical for diagnosing car...

Prediction of Left Atrial Volume Parameters from Resting ECGs and Tabular Data Using Deep Learning in the UK Biobank

We present a deep learning model that predicts left atrial (LA) volume from standard 12-lead ECG rec...

Dual-Phase Cross-Modal Contrastive Learning for CMR-Guided ECG Representations for Cardiovascular Disease Assessment

Cardiac magnetic resonance imaging (CMR) offers detailed evaluation of cardiac structure and functio...

Contrastive Learning for Multi Label ECG Classification with Jaccard Score Based Sigmoid Loss

Recent advances in large language models (LLMs) have enabled the development of multimodal medical A...

ECG-IMN: Interpretable Mesomorphic Neural Networks for 12-Lead Electrocardiogram Interpretation

Deep learning has achieved expert-level performance in automated electrocardiogram (ECG) diagnosis, ...

Leveraging the wearable 1-lead ECG signal: From cardiac rhythm to cardiac function assessment

The electrocardiogram (ECG) is a critical tool in the diagnosis and monitoring of cardiovascular dis...

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 pregn...

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