Myocardial Infarction

Arrhythmias Classification Using Short-Time Fourier Transform and GAN Based Data Augmentation.

Lacking sufficient training samples of different heart rhythms is a common bottleneck to obtain arrhythmias classification models with high accuracy using artificial neural networks. To solve this problem, we propose a novel data augmentation method based on short-time Fourier transform (STFT) and generative adversarial network (GAN) to obtain evenly distributed samples in the training dataset. Fi...

RPnet: A Deep Learning approach for robust R Peak detection in noisy ECG.

Automatic detection of R-peaks in an Electrocardiogram signal is crucial in a multitude of applications including Heart Rate Variability (HRV) analysis and Cardio Vascular Disease(CVD) diagnosis. Although there have been numerous approaches that have successfully addressed the problem, there has been a notable dip in the performance of these existing detectors on ECG episodes that contain noise an...

Potential Prognostic Markers in the Heart Rate Variability Features for Early Diagnosis of Sepsis in the Pediatric Intensive Care Unit using Convolutional Neural Network Classifiers.

Blood infection due to different circumstances could immediately develop to an extreme body reaction that leads to a serious life-threatening conditio...

End-to-End Deep Learning Model for Cardiac Cycle Synchronization from Multi-View Angiographic Sequences.

Dynamic reconstructions (3D+T) of coronary arteries could give important perfusion details to clinicians. Temporal matching of the different views, wh...

Classification of Aortic Stenosis Using ECG by Deep Learning and its Analysis Using Grad-CAM.

This paper proposes an automatic method for classifying Aortic valvular stenosis (AS) using ECG (Electrocardiogram) images by the deep learning whose ...

Multi-level Stress Assessment Using Multi-domain Fusion of ECG Signal.

Stress analysis and assessment of affective states of mind using ECG as a physiological signal is a burning research topic in biomedical signal proces...

Potential Prognostic Markers in the Heart Rate Variability Features for Early Diagnosis of Sepsis in the Pediatric Intensive Care Unit using Convolutional Neural Network Classifiers.

Blood infection due to different circumstances could immediately develop to an extreme body reaction that leads to a serious life-threatening conditio...

Deep learning for comprehensive ECG annotation.

BACKGROUND: Increasing utilization of long-term outpatient ambulatory electrocardiographic (ECG) monitoring continues to drive the need for improved E...

Machine Learning on High-Dimensional Data to Predict Bleeding Post Percutaneous Coronary Intervention.

INTRODUCTION: The purpose of the current study is to determine the accuracy of machine learning in predicting bleeding outcomes post percutaneous coro...

[Detection of inferior myocardial infarction based on densely connected convolutional neural network].

Inferior myocardial infarction is an acute ischemic heart disease with high mortality, which is easy to induce life-threatening complications such as ...

Autonomic perspiration in 3D-printed hydrogel actuators.

In both biological and engineered systems, functioning at peak power output for prolonged periods of time requires thermoregulation. Here, we report a...

Contribution of neural networks in the diagnosis and treatment of cardiac arrhythmia.

Arrhythmia is a dangerous disease in which the heart rhythm varies and it may be very fast or very slow. Rapid heartbeats can lead to shortness of bre...

Machine learning versus traditional risk stratification methods in acute coronary syndrome: a pooled randomized clinical trial analysis.

Traditional statistical models allow population based inferences and comparisons. Machine learning (ML) explores datasets to develop algorithms that d...

Association between Serum Vitamin D Concentration Status and Matrix Metalloproteinase-9 in Patients Undergoing Elective Percutaneous Coronary Intervention.

Cardiovascular diseases (CVD) have become increasingly life-threatening during recent decades. Several studies have shown that matrix metalloproteinas...

Heterogeneity of perception of symptoms in patients with asthma.

BACKGROUND: Cough-dominant or cough-variant asthma is common in Japan. However, it is unclear whether cough and dyspnea, the cardinal symptoms of bron...

Relationship of soluble ST2 to pulmonary hypertension severity in patients undergoing cardiac resynchronization therapy.

BACKGROUND: Pulmonary hypertension (PH) is an adverse prognostic marker in patients undergoing cardiac resynchronization therapy (CRT). We sought to d...

A fitting machine learning prediction model for short-term mortality following percutaneous catheterization intervention: a nationwide population-based study.

BACKGROUND: A suitable multivariate predictor for predicting mortality following percutaneous coronary intervention (PCI) remains undetermined. We use...

Successful Resuscitation of a Young Girl Who Drank Rivastigmine With Respiratory Failure.

Rivastigmine is a non-competitive reversible inhibitor of acetylcholinesterase which is approved as one of the fi rst-line treatment options for Alzhe...

Detection and Classification of Chronic Total Occlusion lesions using Deep Learning.

Cardiovascular disease (CVD) is one of the diseases with the highest mortality rate in modern society, while chronic total occlusion (CTO) is the init...

Deep Learning Based Patient-Specific Classification of Arrhythmia on ECG signal.

The classification of the heartbeat type is an essential function in the automatical electrocardiogram (ECG) analysis algorithm. The guideline of the ...