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Updated: Jun 30, 2025

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基于动态多变量时间序列数据的深度学习模型来预测狼性炎发作

Siwan Huang1, Yinghua Chen2, Yanan Song1

  • 1Ping An Healthcare Technology, Beijing, China.

BMJ open
|March 14, 2024
PubMed
概括

这项研究开发了一种可解释的深度学习模型,用于使用动态时间序列数据预测狼性炎 (LN) 复发. 该模型准确地预测LN复发,有助于临床管理.

关键词:
免疫学 免疫学腎臟病學 (nephrology) 是一種醫學專業.类风湿病学 类风湿病学统计学和研究方法.

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In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
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