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<center><strong>Automated diagnosis of arrhythmia using combination of<br> CNN and LSTM techniques with variable length heart beats
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<p><center>通过CNN-LSTM技术结合可变长度的心拍对心律失常自动诊断</center><br>期刊: Computers in Biology and Medicine </p>
<p>作者: Shu Lih Oh …</p>
<p>日期: 1 November 2018 </p>
<p>原文链接:<a href="http://dx.doi.org/10.1016/j.compbiomed.2018.06.002" target="_blank" rel="noopener">点击</a></p>
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<center><strong>An Effective LSTM Recurrent Network to Detect<br>Arrhythmia on Imbalanced ECG Dataset
</strong></center>
<p><center>在不平衡ECG数据集上检测心律不齐的一个有效LSTM循环网络</center><br>期刊:Journal of Healthcare Engineering </p>
<p>作者:junli Gao …</p>
<p>日期:Published 13 October 2019 </p>
<p>原文链接:<a href="https://doi.org/10.1155/2019/6320651" target="_blank" rel="noopener">点击</a></p>
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<p><center><strong>基于 CNN-BiLSTM 神经网络的8导联ECG时序数据分类的可解释性分析</strong></center></p>
<h3 id="摘要"><a href="#摘要" class="headerlink" title="摘要"></a>摘要</h3><p> 心血管疾病具有危急值属性,通过筛查第一时间发现心电危急值具有重要意义。利用 CNN-BiLSTM模型结合8导联ECG数据的时间特性和空间特征,可以有效地提高特定疾病分类的准确性。首先,利用连续小波变换去除ECG噪声。其次,通过检测R波的峰值位置,提取连续的RR间期。最后,在中国心血管疾病数据库(Chinese Cardiovascular Disease Database,CCDD)中挑选具有较高危急值病种的8导联数据作为对象,使用CNN-BiLSTM算法分类识别,并使用郑州大学第一附属医院多导联临床数据进行验证。结果表明, CNN-BiLSTM模型结合8导联ECG数据的节律和空间特征,比本文讨论的其他方法具有更高的可解释性。 </p>
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<a class="post-title-link" href="/2019/09/26/Interpretability-Analysis-of-Heartbeat-Classification-Based-on-Heartbeat-Activitys-Global-Sequence-Features-and-BiLSTM-Attention-Neural-Network/" itemprop="url">Interpretability Analysis of Heartbeat Classification Based on Heartbeat Activitys Global Sequence Features and BiLSTM-Attention Neural Network</a></h1>
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<center><strong>Interpretability Analysis of Heartbeat Classification Based on Heartbeat Activity’s Global<br> Sequence Features and BiLSTM-Attention Neural Network</strong></center>
<p><center>基于心跳活动的全局序列特征和BiLSTM- Attention神经网络的心跳分类的<font color="#dd0000">可解释性分析</font></center><br>期刊:IEEE Access</p>
<p>作者:RUNCHUAN LI …</p>
<p>日期:August 7, 2019 </p>
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<p>Go Modules 是 Golang 官方最近几个版本推出的原生的包管理方式,在此之前,社区也不乏多种包管理方案。在讨论 Go Modules 之前,我们先回顾一下 Golang 的包管理历史的发展。然后讨论一下 Go Modules 的使用以及一些特性,篇幅有限,有些地方没有深入展开。</p>
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