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An automatic premature ventricular contraction recognition system based on imbalanced dataset and pre-trained residual network using transfer learning on ECG …
The development of automatic monitoring and diagnosis systems for cardiac patients over
the internet has been facilitated by recent advancements in wearable sensor devices from …
the internet has been facilitated by recent advancements in wearable sensor devices from …
Self-Attention MHDNet: A novel deep learning model for the detection of R-peaks in the electrocardiogram signals corrupted with Magnetohydrodynamic effect
Magnetic resonance imaging (MRI) is commonly used in medical diagnosis and minimally
invasive image-guided operations. During an MRI scan, the patient's electrocardiogram …
invasive image-guided operations. During an MRI scan, the patient's electrocardiogram …
HybDeepNet: ECG signal based cardiac arrhythmia diagnosis using a hybrid deep learning model
CS Pandian, AM Kalpana - Information Technology and Control, 2023 - itc.ktu.lt
To monitor electrical indications from the heart and assess its performance, the
electrocardiogram (ECG) is the most common and routine diagnostic instrument employed …
electrocardiogram (ECG) is the most common and routine diagnostic instrument employed …
[PDF][PDF] Self-Attention MHDNet: A Novel Deep Learning Model for the Detection of R-Peaks in the Electrocardiogram Signals Corrupted with Magnetohydrodynamic …
MH Chowdhury, MEH Chowdhury, MS Khan, MA Ullah… - 2023 - academia.edu
Magnetic resonance imaging (MRI) is commonly used in medical diagnosis and minimally
invasive image-guided operations. During an MRI scan, the patient's electrocardiogram …
invasive image-guided operations. During an MRI scan, the patient's electrocardiogram …