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Updated: Jun 9, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

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Published on: December 6, 2024

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使用大人口健康数据库进行预测建模的AI/ML方法和经典回归的比较:应用到COVID-19病例预测中的应用

Lise M Bjerre1,2,3, Cayden Peixoto1, Rawan Alkurd4

  • 1Institut du Savoir Montfort, 713, chemin Montréal, Ottawa, Ontario K1K 0T2, Canada.

Global epidemiology
|October 22, 2024
PubMed
概括

人工智能和机器学习 (AI / ML) 模型,特别是梯度增强树 (GBT),与传统的物流回归相比,在COVID-19病例识别方面显示出更高的预测准确性. 整合症状数据显著提高了所有方法的模型性能.

关键词:
人工智能的人工智能是人工智能.在 COVID-19 疫情中,渐变增强了树木的增长.后勤回归的逻辑回归机器学习 机器学习预测建模的预测建模.

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