Latest AI and machine learning research in arrhythmias for healthcare professionals.
Existing arrhythmia classification methods usually use manual selection of electrocardiogram (ECG) s...
IMPORTANCE: For patients with chronic kidney disease (CKD), hyperkalemia is common, associated with ...
Electrocardiogram (ECG) signals are easily disturbed by internal and external noise, and its morphol...
In order to enhance the accuracy of computer aided electrocardiogram analysis, we propose a deep lea...
Background We developed a new left ventricular hypertrophy ( LVH ) criterion using a machine-learnin...
AIMS: Electrical storm (ES) is a serious arrhythmic syndrome that is characterized by recurrent epis...
OBJECTIVE: To train convolutional networks using multi-lead ECG data and classify new data accuratel...
The number of features that can be extracted from ECG signals has increased with the advancement in ...
Continuous blood pressure (BP) monitoring can produce a significant amount of digital data, which in...
Since 2012, we have been developing a remote-controlled robotic system (ZerobotĀ®) for needle inserti...
This paper presents a study using 1D convolutional neural networks (CNNs) for ECG-based authenticati...
Detection of ECG characteristic points serves as the first step in automated ECG analysis techniques...
Cardiac arrhythmia is known to be one of the most common causes of death worldwide. Therefore, devel...
Heart disease classification based on electrocardiogram(ECG) signal has become a priority topic in t...
In this paper, we propose an end-to-end approach to addressing QRS complex detection and measurement...
Heart rate variability (HRV) analysis is widely used to assess the sympathetic and parasympathetic t...
Atrial fibrillation (AF) is a common health issue, not only in developed countries but also in devel...
Early detection and discrimination of cardiac arrhythmia, atrial fibrillation (AF) in particular, is...
BACKGROUND: Automation in cardiac arrhythmia classification helps medical professionals make accurat...
OBJECTIVES: To collect and analyze the ECG signal in real time, the analog filter and the signal amp...
Widely developed for clinical screening, electrocardiogram (ECG) recordings capture the cardiac elec...