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神经网络用于心电图诊断房颤的研究进展
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Abstract:
房颤的发病具有一定的隐匿性，传统的临床实践对于部分房颤患者的早期识别存在不足；人工智能在心电图领域的应用越来越深入，神经网络模型可以对多种不同的心率失常进行识别和预测。本文就神经网络在心电图诊断房颤方面的新进展作一综述。
Asmany episodes of atrial fibrillation remain asymptomatic, traditional clinical practice has defects in early identification of some patients with atrial fibrillation. Artificial intelligence is widely used in the field of electrocardiogram. Neural network models can identify and predict various kinds of ar-rhythmia. This article reviews the progress of neural network in electrocardiographic diagnosis for atrial fibrillation.
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