论文标题
部分可观测时空混沌系统的无模型预测
Using machine learning algorithms to determine the post-COVID state of a person by his rhythmogram
论文作者
论文摘要
在这项研究中，我们应用了机器学习算法来确定一个人的后盘状态。在研究期间，在心电图数据中发现了一个人的后卵形状态。我们已经证明，患者的ECG信号中的此标记可用于诊断旋转后状态。
In this study we applyed machine-learning algorithms to determine the post-COVID state of a person. During the study, a marker of the post-COVID state of a person was found in the electrocardiogram data. We have shown that this marker in the patient's ECG signal can be used to diagnose a post-COVID state.
