Arrhythmias

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 in detecting cardiac murmurs and arrhythmias compared to fourth-year veterinary students and experienced clinicians. METHODS: Dogs and cats presenting to a university teaching hospital were prospectively enrolled from August 1, 2025, through December 31, 2025. Each animal underwent cardiac ausculta...

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 and neurocognitive risks. While polysomnography remains the clinical gold standard for diagnosis, it is costly and unsuitable for large-scale or real-time screening. Electrocardiogram (ECG) signals offer a non-invasive, low-cost alternative for sleep apnea detection. We present a holistic new framewor...

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, yet current diagnostic paradigms may fail to detec...

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 critical in military operational environments where evacu...

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 and mortality worldwide. While echocardiography r...

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) affects 10%-20% of patients and is a key quality indicat...

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 operate at varying sampling frequencies, directly influ...

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 quality and interpretability in coronary computed tomog...

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-lead ECG data. However, clinical analysis and model...

Validation of a deep learning-based system for sleep staging, arousal detection, and respiratory event scoring in atrial fibrillation patients.

PURPOSE: Obstructive sleep apnea is a common yet underdiagnosed sleep disorder in patients with atrial fibrillation (AF). Although polysomnography (PS...

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 tool for identifying patients with atrial fibrilla...

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 with chest pain remains a major clinical challenge. D...

Large Language Model-Based Localization of Premature Ventricular Contraction Origins: A Retrospective Diagnostic Accuracy Study.

BACKGROUND: Accurate localization of premature ventricular contraction (PVC) origin from 12-lead electrocardiography (ECG) is important for procedural...

AI-Enabled ECG Mapping to Guide Leadless Atrial Pacemaker Implantation in the Bachmann's Bundle Region.

BACKGROUND: Physiologic atrial pacing at the Bachmann's bundle region may improve biatrial synchrony, but accurate implantation of atrial leadless pac...

A deep learning framework for multi-lead ECG arrhythmia classification with CAM interpretability and LLM-driven clinical guidance.

Cardiac arrhythmias remain a major cause of morbidity and mortality, requiring accurate and interpretable automated diagnosis. This reserach presents ...

Joint Multi-Task Deep Learning with Cross-Task Attention for Simultaneous Lesion Segmentation, Detection, and Severity Grading of Diabetic Retinopathy on Fundus Images: An External Validation Study.

BACKGROUND: Diabetic retinopathy (DR) severity is graded from the type and distribution of retinal lesions, yet most automated methods address grading...

Preoperative electrocardiography for predicting cardiovascular events after noncardiac surgery: a secondary analysis of two prospective cohorts.

BACKGROUND: The predictive value of preoperative resting ECGs for cardiovascular events after noncardiac surgery is unclear. This study evaluated whet...

Artificial intelligence shows comparable or improved performance to traditional risk models in predicting atrial fibrillation after cryptogenic stroke.

BACKGROUND AND AIMS: Detecting subclinical atrial fibrillation (AF) and initiating anticoagulation therapy are critical for secondary stroke preventio...

Toward diagnostic precision and context-adaptive therapy in prehospital supraventricular tachycardia.

The recent scoping review by Gamberini et al. provides a comprehensive overview of the prehospital diagnosis and management of supraventricular tachyc...

AI-Driven Atrial Fibrillation Management: From Signal to Strategy.

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia worldwide and is associated with substantial morbidity, including ischemic st...