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Updated: Jan 25, 2026

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深度学习架构用于模拟和预测加纳中风病例

Abdul-Karim Iddrisu1, Morongwa Gabanakgosi1, Abubakar Hudu Siddick2

  • 1Department of Statistics, University of Botswana, Gaborone, Botswana.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
|January 23, 2026
PubMed
概括

加纳面临着很高的中风负担,深度学习模型预测趋势会稳定. 长期短期记忆 (LSTM) 模型在预测未来中风发病率方面被证明是最有效的.

关键词:
贝叶斯的长期短期记忆 (BLSTM)贝叶斯的卷积LSTM ((BConv) 的情况.深度学习是一种深度学习.一次性中风中风中风中风中风

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