Arrhythmias

Opportunistic Screening for Chagas Disease Using an Artificial Intelligence-Enabled ECG: Prospective Evaluation of Feasibility and Diagnostic Accuracy.

BACKGROUND: Chagas disease (ChD), a neglected cardiovascular condition, affects 7.5 to 10.5 million ...

Machine learning-enhanced baseline risk prediction models for cancer therapy related cardiac dysfunction: a systematic review and critical appraisal of methodological quality.

AIMS: Cancer therapy-related cardiac dysfunction (CTRCD) is a prevalent complication with adverse cl...

Letter by Li et al Regarding Article, "Deep Learning-Based Continuous QT Monitoring to Identify High-Risk Prolongation Events After Class III Antiarrhythmic Initiation".

Response by Rogers et al to Letter Regarding, "Deep Learning-Based Continuous QT Monitoring to Identify High-Risk Prolongation Events After Class III Antiarrhythmic Initiation".

Utility of ECG-Vision for Surveillance of Left Ventricular Dysfunction in Patients With Hypertrophic Cardiomyopathy Initiated on Mavacamten.

BACKGROUND: Frequent transthoracic echocardiograms (TTEs) are required to monitor for left ventricul...

Value of the 12-lead ECG to localize the origin of ventricular tachycardia.

The 12-lead electrocardiogram (ECG) recorded during ventricular tachycardia (VT) remains a simple, u...

A multi-band spatial asymmetry convolutional neural network for EEG-based emotion recognition.

Emotion recognition is an important component for enabling machines to perceive and respond to human...

Enhancing cardiovascular disease diagnosis through knowledge distillation and hybrid Transformer-CNN-SENet architecture.

Worldwide, cardiovascular diseases (CVDs) are the leading cause of mortality, making early detection...

Assessment and validation of the established free-running framework for cardiac function by magnetic resonance imaging at 1.5T (FAST-CMR): an international multi-center, multi-vendor study.

BACKGROUND: Cardiovascular magnetic resonance (CMR) is the reference standard for assessing cardiac ...

An autonomous multimodal AI agent for evidence-grounded ophthalmic diagnosis.

Multimodal ophthalmic diagnosis requires integrating fundus photography, B-scan ultrasonography, and...

An artificial intelligence-enabled digital stethoscope demonstrates moderate murmur detection in dogs but not cats and unreliable arrhythmia classification in both species.

OBJECTIVE: To prospectively evaluate the diagnostic performance of an AI-enabled digital stethoscope...

A multifaceted approach for obstructive sleep apnea classification from ECG signal using deep learning.

Obstructive sleep apnea (OSA) is a common sleep disorder associated with increased cardiovascular an...

Does Maximum Troponin T Value Correlate With Acute Coronary Occlusion Among Patients Treated as NSTEMI?

BACKGROUND: Occlusion myocardial infarction (OMI) is increasingly recognized among NSTEMI patients, ...

AI-Assisted Electrocardiogram Interpretation Improves ST-Elevation Myocardial Infarction Diagnostic Accuracy Among Advanced Practice Providers: A Prospective Randomized Crossover Study.

INTRODUCTION: Timely and accurate diagnosis of ST-elevation myocardial infarction (STEMI) is critica...

MMMuLNet: Multimodal Mutual Deep learning Framework for the Pediatric Congenital Heart Disease Detection.

Congenital heart disease (CHD) is the most common birth defect and a major cause of infant morbidity...

Nurse-Led Large Language Model Chatbot for Predicting and Preventing Complications After Coronary Artery Bypass Grafting: Protocol for a Randomized Controlled Trial.

BACKGROUND: Thirty-day unplanned readmission following coronary artery bypass grafting (CABG) affect...

Sampling Frequency Has Architecture-Dependent Effects on ECG Deep Learning Classification: CNNs Are Robust, Transformers Benefit Modestly.

BACKGROUND: Electrocardiograms are deployed across a wide range of environments and frequently opera...

CCTA without ECG Leads Using Whole-Heart Motion Correction Algorithm Based on Wide-Detector CT.

PURPOSE: This study evaluates the impact of a whole heart motion correction algorithm on image quali...

Efficient ECG Representation Learning via Intervention-Based Attribution Alignment.

The widespread adoption of wearable ECG devices has driven an explosive growth of long-term, multi-l...

Clinical and Echocardiographic Factors Associated With AI-Estimated Atrial Fibrillation Likelihood During Sinus Rhythm in Patients With Documented Paroxysmal Atrial Fibrillation.

BACKGROUND: Artificial intelligence-enabled electrocardiography (AI-ECG) has emerged as a promising ...

Deep learning electrocardiogram analysis for rapid rule-out of acute coronary syndrome in the emergency department: a multicenter diagnostic accuracy study.

BACKGROUND: Rapid and accurate exclusion of acute coronary syndrome (ACS) in patients presenting wit...