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基于短期长期记忆的预测,使用监测和气象数据在日本东京的流感流行病

Daiki Koge1,2, Keita Wagatsuma2,3

  • 1Division of Bioinformatics, Department of Information Science, Graduate School of Science and Technology, Niigata University, Niigata, Japan.

Frontiers in public health
|September 8, 2025
PubMed
概括

这项研究开发了一种长期短期记忆 (LSTM) 模型,用于准确地预测东京每周的流感. 整合气象数据和公共假日显著提高了公共卫生规划的预测准确性.

关键词:
日本 日本 日本 日本 日本.气候变化 气候变化 气候变化流行病学流行病学预测 预测 预测 预测流感 流感 流感 流感 流感气象因素是气象因素.

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