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About Cardiac Arrhythmia Detection Using Deep Learning
The document discusses using deep learning techniques to detect cardiac arrhythmias from electrocardiogram (ECG) data. Specifically, it proposes applying a deep learning framework trained on general images to classify patient ECGs into different cardiac conditions. The methodology involves preprocessing ECG data, extracting features directly from the data using convolutional neural networks, and classifying rhythms into normal, premature ventricular contraction, atrial fibrillation, or other types. The goal is to develop an accurate, easy-to-use system for automatic ECG arrhythmia detection.
Detailed Information
Author: | ['Revati Wable'] |
---|---|
Publication Year: | 2021 |
Pages: | 9 |
Language: | English |
Format: | |
Price: | FREE |
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