Myocardial Infarction

Assessment of the long RR intervals using convolutional neural networks in single-lead long-term Holter electrocardiogram recordings.

Advancements in medical technology have extended long-term electrocardiogram (ECG) monitoring from t...

ECG Sensor Design Assessment with Variational Autoencoder-Based Digital Watermarking.

Designing an ECG sensor circuit requires a comprehensive approach to detect, amplify, filter, and co...

Explainable machine learning model based on EEG, ECG, and clinical features for predicting neurological outcomes in cardiac arrest patient.

Early and accurate prediction of neurological outcomes in comatose patients following cardiac arrest...

An Energy-Efficient Configurable 1-D CNN-Based Multi-Lead ECG Classification Coprocessor for Wearable Cardiac Monitoring Devices.

Many electrocardiogram (ECG) processors have been widely used for cardiac monitoring. However, most ...

Preoperative Factors Associated With In-Hospital Major Bleeding After Percutaneous Coronary Intervention: A Systematic Review.

BACKGROUND: Preoperative risk assessment of bleeding after percutaneous coronary intervention (PCI) ...

Electrocardiographic Discrimination of Long QT Syndrome Genotypes: A Comparative Analysis and Machine Learning Approach.

Long QT syndrome (LQTS) presents a group of inheritable channelopathies with prolonged ventricular r...

Identification of biomarkers associated with M1 macrophages in the ST-segment elevation myocardial infarction through bioinformatics and machine learning approaches.

ST-segment elevation myocardial infarction (STEMI) is considered a critical cardiac condition with a...

Integrating deep learning with ECG, heart rate variability and demographic data for improved detection of atrial fibrillation.

BACKGROUND: Atrial fibrillation (AF) is a common but often undiagnosed condition, increasing the ris...

AI-ECG Supported Decision-Making for Coronary Angiography in Acute Chest Pain: The QCG-AID Study.

This pilot study evaluates an artificial intelligence (AI)-assisted electrocardiography (ECG) analys...

Artificial-intelligence-enhanced ECG: a potential solution to limitations of ECG in detecting left ventricular dysfunction after chemotherapy.

ZnO nanoflower-mediated paper-based electrochemical biosensor for perfect classification of cardiac biomarkers with physics-informed machine learning.

The widespread exposure of acute myocardial infarction globally demands an ultrasensitive, rapid, an...

Synthetic ECG signal generation using generative neural networks.

Electrocardiogram (ECG) datasets tend to be highly imbalanced due to the scarcity of abnormal cases....

A multicenter pragmatic implementation study of AI-ECG-based clinical decision support software to identify low LVEF: Clinical trial design and methods.

BACKGROUND: Artificial intelligence (AI) enabled algorithms can detect or predict cardiovascular con...

Automated Identification of Stroke Thrombolysis Contraindications from Synthetic Clinical Notes: A Proof-of-Concept Study.

INTRODUCTION: Timely thrombolytic therapy improves outcomes in acute ischemic stroke. Manual chart r...

Extraction of fetal heartbeat locations in abdominal phonocardiograms using deep attention transformer.

Assessing fetal health traditionally involves techniques like echocardiography, which require skille...

Automated detection of arrhythmias using a novel interpretable feature set extracted from 12-lead electrocardiogram.

The availability of large-scale electrocardiogram (ECG) databases and advancements in machine learni...

Multimodal machine learning for deception detection using behavioral and physiological data.

Deception detection is crucial in domains like national security, privacy, judiciary, and courtroom ...

A deep Bi-CapsNet for analysing ECG signals to classify cardiac arrhythmia.

- In recent times, the electrocardiogram (ECG) has been considered as a significant and effective sc...

A brief history and clinical use of robotic procedures in the cardiovascular system.

Robotic-assisted percutaneous coronary intervention (r-PCI) exemplifies the advancement of intervent...

Reconstruction of ECG from ballistocardiogram using generative adversarial networks with attention.

Electrocardiogram (ECG) is widely used to provide early warning signals for cardiovascular diseases....

Machine learning analysis of integrated ABP and PPG signals towards early detection of coronary artery disease.

Every year, Coronary Artery Disease (CAD) claims lives of over a million people. CAD occurs when the...