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This document discusses methods for detecting cardiovascular diseases from electrocardiogram (ECG) images using machine learning and deep learning. It begins by introducing the importance of early detection of cardiovascular diseases. It then discusses using deep learning techniques like convolutional neural networks (CNNs) to classify four types of cardiac conditions from ECG images. Specifically, it proposes a new CNN architecture for cardiac abnormality prediction. Experimental results show the proposed CNN model achieves 98.23% accuracy for classification, outperforming other methods. When used for feature extraction, it achieves 99.79% accuracy with Naive Bayes classification.
Detailed Information
| Author: | ['PENTAMALLA HARIHARAN'] |
|---|---|
| Publication Year: | 2024 |
| Pages: | 10 |
| Language: | English |
| Format: | |
| Price: | FREE |
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