Wearable devices have received significant attention recently for their ability to monitor
critical physiological signals noninvasively, such as electrocardiography …

Learning representations from electrocardiogram (ECG) signals can serve as a fundamental
step for different machine learning-based ECG tasks. In order to extract general ECG …

QRS 波群形态识别是心电异常检测的关键环节, 是疾病诊断的主要依据. 目前的QRS
波群形态识别方法存在识别出的形态较少, 对参数敏感等问题. 为此, 提出一种基于隐马尔科夫的 …

QRS 波群形态识别是心电异常检测的关键环节, 是疾病诊断的主要依据. 目前的QRS
波群形态识别方法存在识别出的形态较少, 对参数敏感等问题. 为此, 提出一种基于隐马尔科夫的 …

Learning representations from electrocardiogram (ECG) serves as a fundamental step for
many downstream machine learning-based ECG analysis tasks. However, the learning …

Cardiac abnormalities are one of the leading causes of mortality and morbidity among the
population. Changes in the morphology and rhythm of the cardiac signals associated with …

Data mining of clinical data has big feasibility for refining the quality of hospital remedy and
increasing survival probability of patients. Data-driven prediction techniques rely heavily on …

Access to essential services determines individuals' ability to meet health, safety, and social
needs that enable them to thrive in their daily lives. But such access is not evenly distributed …

The morphological identification of QRS complex is a key in the detection of abnormal ECG,
which acts as the basis for disease diagnosis. The existing QRS morphological recognition …

Cardiovascular diseases are the leading cause of death worldwide, claiming approximately
17.9 million lives each year. In this study, a novel CAD system to detect and classify …