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Arrhythmias, Cardiac

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Deep learning based ECG segmentation for delineation of diverse arrhythmias.

PloS one
Accurate delineation of key waveforms in an ECG is a critical step in extracting relevant features to support the diagnosis and treatment of heart conditions. Although deep learning based methods using segmentation models to locate P, QRS, and T wave...

Arrhythmia detection by the graph convolution network and a proposed structure for communication between cardiac leads.

BMC medical research methodology
One of the most common causes of death worldwide is heart disease, including arrhythmia. Today, sciences such as artificial intelligence and medical statistics are looking for methods and models for correct and automatic diagnosis of cardiac arrhythm...

Cardiac Arrhythmia Classification Using Advanced Deep Learning Techniques on Digitized ECG Datasets.

Sensors (Basel, Switzerland)
ECG classification or heartbeat classification is an extremely valuable tool in cardiology. Deep learning-based techniques for the analysis of ECG signals assist human experts in the timely diagnosis of cardiac diseases and help save precious lives. ...

Heart patient health monitoring system using invasive and non-invasive measurement.

Scientific reports
The abnormal heart conduction, known as arrhythmia, can contribute to cardiac diseases that carry the risk of fatal consequences. Healthcare professionals typically use electrocardiogram (ECG) signals and certain preliminary tests to identify abnorma...

Applying Artificial Intelligence for Phenotyping of Inherited Arrhythmia Syndromes.

The Canadian journal of cardiology
Inherited arrhythmia disorders account for a significant proportion of sudden cardiac death, particularly among young individuals. Recent advances in our understanding of these syndromes have improved patient diagnosis and care, yet certain clinical ...

Classification Method of ECG Signals Based on RANet.

Cardiovascular engineering and technology
BACKGROUND: Electrocardiograms (ECG) are an important source of information on human heart health and are widely used to detect different types of arrhythmias.

Application of artificial intelligence in the diagnosis and treatment of cardiac arrhythmia.

Pacing and clinical electrophysiology : PACE
The rapid growth in computational power, sensor technology, and wearable devices has provided a solid foundation for all aspects of cardiac arrhythmia care. Artificial intelligence (AI) has been instrumental in bringing about significant changes in t...

Energy-efficient dynamic sensor time series classification for edge health devices.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Time series data plays a crucial role in the realm of the Internet of Things Medical (IoMT). Through machine learning (ML) algorithms, online time series classification in IoMT systems enables reliable real-time disease dete...

ECG autoencoder based on low-rank attention.

Scientific reports
The prevalence of cardiovascular disease (CVD) has surged in recent years, making it the foremost cause of mortality among humans. The Electrocardiogram (ECG), being one of the pivotal diagnostic tools for cardiovascular diseases, is increasingly gai...

Automatic detection of cardiac conditions from photos of electrocardiogram captured by smartphones.

Heart (British Cardiac Society)
BACKGROUND: Researchers have developed machine learning-based ECG diagnostic algorithms that match or even surpass cardiologist level of performance. However, most of them cannot be used in real-world, as older generation ECG machines do not permit i...