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Updated: Jun 9, 2025

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在基于机器学习技术的畜牧业强化下,人类血病的时空空间风险在中国西省的畜牧业强化

Li Shen1, Chenghao Jiang1, Fangting Weng1

  • 1School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China.

Epidemiology and infection
|October 24, 2024
PubMed
概括

机器学习模型在中国准确预测了人类血清病 (HB). ConvLSTM模型表现最好,确定气候和畜牧业的强化是HB传播的关键驱动因素.

关键词:
人类菌病人类菌病影响因素的影响因素.机器学习技术 机器学习技术风险预测风险预测

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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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