Cardiovascular

Myocardial Infarction

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

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Over-fitting suppression training strategies for deep learning-based atrial fibrillation detection.

Nowadays, deep learning-based models have been widely developed for atrial fibrillation (AF) detecti...

An IoT and Fog Computing-Based Monitoring System for Cardiovascular Patients with Automatic ECG Classification Using Deep Neural Networks.

Telemedicine and all types of monitoring systems have proven to be a useful and low-cost tool with a...

Identification of Sleep Apnea Severity Based on Deep Learning from a Short-term Normal ECG.

BACKGROUND: This paper proposes a novel method for automatically identifying sleep apnea (SA) severi...

Identification of dental pain sensation based on cardiorespiratory signals.

The aim of this study is to investigate the feasibility of the detection of brief periods of pain se...

Explainable artificial intelligence to detect atrial fibrillation using electrocardiogram.

INTRODUCTION: Early detection and intervention of atrial fibrillation (AF) is a cornerstone for effe...

Artificial neural network based prediction of postthrombolysis intracerebral hemorrhage and death.

Despite the salient benefits of the intravenous tissue plasminogen activator (tPA), symptomatic intr...

Estimation of End-Diastole in Cardiac Spectral Doppler Using Deep Learning.

Electrocardiogram (ECG) is often used together with a spectral Doppler ultrasound to separate heart ...

Artificial intelligence algorithm for detecting myocardial infarction using six-lead electrocardiography.

Rapid diagnosis of myocardial infarction (MI) using electrocardiography (ECG) is the cornerstone of ...

Deep learning for digitizing highly noisy paper-based ECG records.

Electrocardiography (ECG) is essential in many heart diseases. However, some ECGs are recorded by pa...

Influence of Optimization Design Based on Artificial Intelligence and Internet of Things on the Electrocardiogram Monitoring System.

With the increasing emphasis on remote electrocardiogram (ECG) monitoring, a variety of wearable rem...

Thrombolysis of Pulmonary Emboli via Endobronchial Ultrasound-Guided Transbronchial Needle Injection.

BACKGROUND: Endobronchial ultrasound-guided transbronchial needle injection (EBUS-TBNI) is a novel t...

Substrate-Free Multilayer Graphene Electronic Skin for Intelligent Diagnosis.

Current wearable sensors are fabricated with substrates, which limits the comfort, flexibility, stre...

Artificial intelligence algorithm for predicting cardiac arrest using electrocardiography.

BACKGROUND: In-hospital cardiac arrest is a major burden in health care. Although several track-and-...

DDxNet: a deep learning model for automatic interpretation of electronic health records, electrocardiograms and electroencephalograms.

Effective patient care mandates rapid, yet accurate, diagnosis. With the abundance of non-invasive d...

Real-Time Cuffless Continuous Blood Pressure Estimation Using Deep Learning Model.

Blood pressure monitoring is one avenue to monitor people's health conditions. Early detection of ab...

Cardiac Troponin Is Elevated in Patients with Thyrotoxicosis and Decreases as Thyroid Function Improves and Brain Natriuretic Peptide Levels Decrease.

INTRODUCTION: High-sensitive cardiac troponin reflects micro-myocardial injury in the absence of ove...

Prediction of Sudden Cardiac Death Risk with a Support Vector Machine Based on Heart Rate Variability and Heartprint Indices.

Most methods for sudden cardiac death (SCD) prediction require long-term (24 h) electrocardiogram re...

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