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Updated: Jun 12, 2025

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深度学习为COVID-19预测注入了SIRVD模型:XGBoost-SIRVD-LSTM方法

Hisham Alkhalefah1, D Preethi2, Neelu Khare3

  • 1Advanced Manufacturing Institute, King Saud University, Riyadh, Saudi Arabia.

Frontiers in medicine
|September 18, 2024
PubMed
概括

这项研究引入了一种新的XGBoost-SIRVD-LSTM模型,用于准确的COVID-19预测. 它结合了数学和机器学习,改善了公共卫生决策的流行病预测.

关键词:
在 COVID-19 疫情中,深度学习是一种深度学习.极端梯度提升 (XGBoost) 的方法功能选择 功能选择长时间的短期记忆 (LSTM)预测 预测 预测 预测易受感染者-康复者-疫苗接种死亡者 (SIRVD)

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