遇见数据集

PhysioNet Challenge 2021

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arXiv2025-09-30 收录
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该数据集是一个面向公众的电生理图(ECG)研究数据集,旨在诊断广泛的心脏异常。它由七个子数据集组成,这些子数据集在人口统计特征上存在差异。具体包括五个用于实验的数据集:PTB-XL、Chapman-Shaoxing、Ningbo、G12EC和CPSC2018。该数据集规模宏大,包含了来自多个子数据集的超过1000份ECG记录。研究任务是对26种心律失常类别进行多标签分类(尤其关注七种常见类别)。

This is a publicly available electrocardiogram (ECG) research dataset designed to diagnose a wide range of cardiac abnormalities. It consists of seven sub-datasets that differ in their demographic characteristics. Specifically, five of these sub-datasets are intended for experimental use: PTB-XL, Chapman-Shaoxing, Ningbo, G12EC, and CPSC2018. This large-scale dataset contains over 1,000 ECG records from multiple sub-datasets. The primary research task of this dataset is multi-label classification for 26 arrhythmia categories, with particular focus on seven common categories.

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Physionet
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PhysioNet Challenge 2021 数据集图片
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