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基于可解释混合深度学习模型的心电图分类研究:面向心脏疾病诊断 ...
本文提出了一种创新的可解释混合深度学习框架,通过结合自编码器(Autoencoder)降维、长短期记忆网络(LSTM)与卷积神经网络(CNN)特征提取,以及多头注意力机制(Multi-head Attention),实现了心电图(ECG)信号的高精度分类。该模型在MIT-BIH和PTBDB数据集上F1 ...
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