Providing reliable detection of QRS complexes is key in automated analyses of electrocardiograms (ECG). Accurate and timely R-peak detections provide a basis for ECG-based diagnoses and to synchronize radiologic, electrophysiologic, or other medical ...
The objective of this study is to explore new imaging techniques with the use of the deep learning method for the identification of cardiac abnormalities present in electrocardiogram (ECG) signals with 2, 3, 4, 6 and 12-lead in the framework of the P...
OBJECTIVE: To demonstrate early aging in patients with lamin A/C (LMNA) gene mutations after hypothesizing that they have a biological age older than chronological age, as such a finding impacts care.
Cardiac disease is the leading cause of death in the US. Accurate heart disease detection is critical to timely medical treatment to save patients' lives. Routine use of the electrocardiogram (ECG) is the most common method for physicians to assess t...
IEEE journal of biomedical and health informatics
Feb 3, 2023
Generative Adversarial Networks (GANs) are a revolutionary innovation in machine learning that enables the generation of artificial data. Artificial data synthesis is valuable especially in the medical field where it is difficult to collect and annot...
Deep neural networks have shown promise in image reconstruction tasks, although often on the premise of large amounts of training data. In this paper, we present a new approach to exploit the geometry and physics underlying electrocardiographic imagi...
OBJECTIVE: To study the relationship between the sex probability derived from the artificial intelligence (AI)-augmented electrocardiogram (ECG) and sex hormone levels.
Automated electrocardiogram (ECG) classification using machine learning (ML) is extensively utilized for arrhythmia detection. Contemporary ML algorithms are typically deployed on the cloud, which may not always meet the availability and privacy requ...
BACKGROUND: Pulmonary hypertension (PH) is life-threatening, and often diagnosed late in its course. We aimed to evaluate if a deep learning approach using electrocardiogram (ECG) data alone can detect PH and clinically important subtypes. We asked: ...
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