A systematic review on the impact of artificial intelligence on electrocardiograms in cardiology
Background Artificial intelligence (AI) has revolutionized numerous industries, enhancing
efficiency, scalability, and insight generation. In cardiology, particularly through …
efficiency, scalability, and insight generation. In cardiology, particularly through …
Detection of congestive heart failure based on Gramian angular field and two-dimensional symbolic phase permutation entropy
J Yang, C Xi - Biocybernetics and Biomedical Engineering, 2024 - Elsevier
Congestive heart failure (CHF) is a serious threat to human health. Electrocardiogram (ECG)
signals have been proven to be useful in the detection of CHF. However, the low amplitude …
signals have been proven to be useful in the detection of CHF. However, the low amplitude …
A deep learning strategy for automatic congestive heart failure detection using novel bottleneck attention module
J Wang, X Guo - Applied Intelligence, 2024 - Springer
Congestive heart failure (CHF) is a sort of common cardiovascular disease. Artificial vision
inspection on electrocardiogram (ECG) has turned into the mainstream diagnosis strategy …
inspection on electrocardiogram (ECG) has turned into the mainstream diagnosis strategy …
A category incremental continuous learning model for imbalance arrhythmia detection
J Feng, Y Si, M Sun, Y Zhang - Measurement Science and …, 2024 - iopscience.iop.org
The development of efficient arrhythmia detection systems is crucial for physiological
measurements and computer-aided diagnosis. Existing systems rely mainly on offline …
measurements and computer-aided diagnosis. Existing systems rely mainly on offline …
Diagnosis of Cardiovascular Disease Based on Class-Incremental Deep and Broad Learning System
M Sun, Y Si, W Fan, Y Wang, L Zhou… - 2024 43rd Chinese …, 2024 - ieeexplore.ieee.org
Early diagnosis of cardiovascular disease can significantly improve patient survival rates.
Existing ECG classification research only considers offline mode, which cannot adapt to new …
Existing ECG classification research only considers offline mode, which cannot adapt to new …