Technology and health care : official journal of the European Society for Engineering and Medicine
39973841
BackgroundDeep neural networks (DNNs) have recently been significantly applied to automatic arrhythmia classification. However, their classification accuracy still has room for improvement.ObjectivesThe aim of this study is to address the existing li...
Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
39993978
In recent years, cardiovascular disease has become a common disease. With the development of machine learning and big data technologies, the processing ability of electrocardiogram (ECG) signals has been greatly enhanced through new computer technolo...
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
40000169
Cardiovascular diseases and psychological disorders represent two major threats to human physical and mental health. Research on electrocardiogram (ECG) signals offers valuable opportunities to address these issues. However, existing methods are cons...
British journal of hospital medicine (London, England : 2005)
39998146
The classification and treatment of myocardial infarction (MI) have evolved significantly over the past few decades, with the ST-segment elevation myocardial infarction (STEMI)/non-STEMI (NSTEMI) paradigm dominating clinical practice. While STEMI, id...
This paper reviews the recent advancements in the application of deep learning combined with electrocardiography (ECG) within the domain of cardiovascular diseases, systematically examining 198 high-quality publications. Through meticulous categoriza...
BACKGROUND/AIMS: Atrial fibrillation (AF) significantly contributes to global morbidity and mortality. Paroxysmal atrial fibrillation (PAF) is particularly common among patients with cryptogenic strokes or transient ischemic attacks and has a silent ...
BACKGROUND: The stroke risk in patients with subclinical atrial fibrillation (AF) is underestimated. By identifying patients at high risk of embolic stroke, health-care professionals can make more informed decisions regarding anticoagulation treatmen...
International journal of medical informatics
39986123
BACKGROUND: Despite the proliferation of heart failure (HF) mortality prediction models, their practical utility is limited. Addressing this, we utilized a significant dataset to develop and validate a deep learning artificial intelligence (AI) model...
The limited availability of labeled ECG data restricts the application of supervised deep learning methods in ECG detection. Although existing self-supervised learning approaches have been applied to ECG analysis, they are predominantly image-based, ...
PURPOSE OF REVIEW: This review explores the role of artificial intelligence (AI) in cardio-oncology, focusing on its latest application across problems in diagnosis, prognosis, risk stratification, and management of cardiovascular (CV) complications ...