Myocardial Infarction

Application of deep learning techniques for heartbeats detection using ECG signals-analysis and review.

Deep learning models have become a popular mode to classify electrocardiogram (ECG) data. Investigat...

End-to-End Deep Learning Fusion of Fingerprint and Electrocardiogram Signals for Presentation Attack Detection.

Although fingerprint-based systems are the commonly used biometric systems, they suffer from a criti...

Cloud-based ECG monitoring using event-driven ECG acquisition and machine learning techniques.

An approach is proposed for the detection of chronic heart disorders from the electrocardiogram (ECG...

Deep Neural Oracles for Short-Window Optimized Compressed Sensing of Biosignals.

The recovery of sparse signals given their linear mapping on lower-dimensional spaces can be partiti...

Going Deep With ECG and Aortic Stenosis: Touchdown or Incomplete Pass?

Deep Learning-Based Algorithm for Detecting Aortic Stenosis Using Electrocardiography.

Background Severe, symptomatic aortic stenosis (AS) is associated with poor prognoses. However, earl...

Non-Standardized Patch-Based ECG Lead Together With Deep Learning Based Algorithm for Automatic Screening of Atrial Fibrillation.

This study was to assess the feasibility of using non-standardized single-lead electrocardiogram (EC...

Automatic Detection of Arrhythmia Based on Multi-Resolution Representation of ECG Signal.

Automatic detection of arrhythmia is of great significance for early prevention and diagnosis of car...

Climate-induced thermoregulatory responses in a non-linear thermal environment: investigating the inter-dependencies using a facile artificial neural network-based predictive strategy.

. Given the burgeoning impacts of climatic variability on human health, suitable computational parad...

Deep learning models for electrocardiograms are susceptible to adversarial attack.

Electrocardiogram (ECG) acquisition is increasingly widespread in medical and commercial devices, ne...

Usefulness of Machine Learning-Based Detection and Classification of Cardiac Arrhythmias With 12-Lead Electrocardiograms.

BACKGROUND: Deep-learning algorithms to annotate electrocardiograms (ECGs) and classify different ty...

ECG Authentication Hardware Design With Low-Power Signal Processing and Neural Network Optimization With Low Precision and Structured Compression.

Biometrics such as facial features, fingerprint, and iris are being used increasingly in modern auth...

A Review of Algorithm & Hardware Design for AI-Based Biomedical Applications.

This paper reviews the state of the arts and trends of the AI-Based biomedical processing algorithms...

Assessing and Mitigating Bias in Medical Artificial Intelligence: The Effects of Race and Ethnicity on a Deep Learning Model for ECG Analysis.

BACKGROUND: Deep learning algorithms derived in homogeneous populations may be poorly generalizable ...

Simultaneous multiple features tracking of beats: A representation learning approach to reduce false alarm rates in ICUs.

The high rate of false alarms is a key challenge related to patient care in intensive care units (IC...

End-to-end trained encoder-decoder convolutional neural network for fetal electrocardiogram signal denoising.

OBJECTIVE: Non-invasive fetal electrocardiography has the potential to provide vital information for...

Machine Learning for Detecting Early Infarction in Acute Stroke with Non-Contrast-enhanced CT.

Background Identifying the presence and extent of infarcted brain tissue at baseline plays a crucial...

Machine Learning Approach to Identify Stroke Within 4.5 Hours.

Background and Purpose- We aimed to investigate the ability of machine learning (ML) techniques anal...

Comprehensive electrocardiographic diagnosis based on deep learning.

Cardiovascular disease (CVD) is the leading cause of death worldwide, and coronary artery disease (C...

Transfer Learning in ECG Classification from Human to Horse Using a Novel Parallel Neural Network Architecture.

Automatic or semi-automatic analysis of the equine electrocardiogram (eECG) is currently not possibl...

Precision Medicine and Artificial Intelligence: A Pilot Study on Deep Learning for Hypoglycemic Events Detection based on ECG.

Tracking the fluctuations in blood glucose levels is important for healthy subjects and crucial diab...