Myocardial Infarction

Adjusting the dose in paediatric care: dispersing four different aspirin tablets and taking a proportion.

OBJECTIVES: When caring for children in a hospital setting, tablets are often manipulated at the war...

Electrocardiogram Classification Based on Faster Regions with Convolutional Neural Network.

The classification of electrocardiograms (ECG) plays an important role in the clinical diagnosis of ...

Combining deep neural networks and engineered features for cardiac arrhythmia detection from ECG recordings.

OBJECTIVE: We aim to combine deep neural networks and engineered features (hand-crafted features bas...

I-Vector-Based Patient Adaptation of Deep Neural Networks for Automatic Heartbeat Classification.

Automatic classification of electrocardiogram (ECG) signals is important for diagnosing heart arrhyt...

A novel IRBF-RVM model for diagnosis of atrial fibrillation.

BACKGROUND AND OBJECTIVE: Atrial fibrillation (AF) is one of the common cardiovascular diseases, and...

Mixed convolutional and long short-term memory network for the detection of lethal ventricular arrhythmia.

Early defibrillation by an automated external defibrillator (AED) is key for the survival of out-of-...

Ventricular geometry-regularized QRSd predicts cardiac resynchronization therapy response: machine learning from crosstalk between electrocardiography and echocardiography.

Up to one-third of patients selected by current guidelines do not respond to cardiac resynchronizati...

A new approach for arrhythmia classification using deep coded features and LSTM networks.

BACKGROUND AND OBJECTIVE: For diagnosis of arrhythmic heart problems, electrocardiogram (ECG) signal...

A RR interval based automated apnea detection approach using residual network.

BACKGROUND AND OBJECTIVE: Apnea is one of the most common conditions that causes sleep-disorder brea...

An Efficient Cardiac Arrhythmia Onset Detection Technique Using a Novel Feature Rank Score Algorithm.

The interpretation of various cardiovascular blood flow abnormalities can be identified using Electr...

Electrocardiogram generation with a bidirectional LSTM-CNN generative adversarial network.

Heart disease is a malignant threat to human health. Electrocardiogram (ECG) tests are used to help ...

Deep Learning in the Prediction of Ischaemic Stroke Thrombolysis Functional Outcomes: A Pilot Study.

RATIONALE AND OBJECTIVES: Intravenous thrombolysis decision-making and obtaining of consent would be...

Assessment of Electrocardiogram Rhythms by GoogLeNet Deep Neural Network Architecture.

The aim of this study is to design GoogLeNet deep neural network architecture by expanding the kerne...

A novel ECG signal compression method using spindle convolutional auto-encoder.

BACKGROUND AND OBJECTIVES: With rapid development of telehealth system and cloud platform, tradition...

ECG Multilead Interval Estimation Using Support Vector Machines.

This work reports a multilead interval measurement algorithm for a high-resolution digital electroc...

A Novel CNN-Based Framework for Classification of Signal Quality and Sleep Position from a Capacitive ECG Measurement.

The further exploration of the capacitive ECG (cECG) is hindered by frequent fluctuations in signal ...

Detecting changes in facial temperature induced by a sudden auditory stimulus based on deep learning-assisted face tracking.

Thermal Imaging (Infrared-Imaging-IRI) is a promising new technique for psychophysiological research...

Artificial intelligence-augmented ECG assessment: The promise and the challenge.

A Machine Learning Approach for Classifying Ischemic Stroke Onset Time From Imaging.

Current clinical practice relies on clinical history to determine the time since stroke (TSS) onset....

Serial electrocardiography to detect newly emerging or aggravating cardiac pathology: a deep-learning approach.

BACKGROUND: Serial electrocardiography aims to contribute to electrocardiogram (ECG) diagnosis by co...

Ultrasensitive sandwich-type immunosensor for cardiac troponin I based on enhanced electrocatalytic reduction of HO using β-cyclodextrins functionalized 3D porous graphene-supported Pd@Au nanocubes.

In this study, Pd@Au nanocubes supported β-cyclodextrins functionalized three-dimensional porous gra...