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基于可解释深度学习的心电图心律失常预测框架:ECG-CNNTX模型在PVC ...
本研究针对心电图(ECG)心律失常人工诊断效率低、易出错的问题,开发了一种将ECG信号转化为二维图像并结合EfficientNetB0与Transformer的混合深度学习框架ECG-CNNTX。该模型在MIT-BIH数据库的PVC检测中达到99%的准确率,并通过Grad-CAM实现可视化解释,为临床提供高精度 ...
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