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Ogive Graph01:07

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An ogive graph is sometimes called a cumulative frequency polygon. It is one type of frequency polygon that shows cumulative frequency. In other words, the cumulative percentages are added to the graph from left to right. An ogive graph plots cumulative frequency on the vertical y-axis and class boundaries along the horizontal x-axis. It’s very similar to a histogram; only instead of rectangles, an ogive displays a single point where the top right of the rectangle would be. Creating this...
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As the name suggests, a multiple bar graph is the same as a bar graph but has multiple bars to depict relationships between different data values. One can include as many parameters as possible. However, each parameter must have the same unit of measurement.
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Proteins are involved in several cellular processes and biochemical reactions. Analyzing a specific protein of interest requires it to be isolated from the other proteins in the cell. This is achieved by overexpressing the specific gene in a suitable host to produce large quantities of the target protein. A tag or label is recombined with the gene to produce a fusion protein containing the target protein and the tag. The tags on these fusion proteins can then be used for easy detection and...
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Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is...
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相关实验视频

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Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
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使用语义上增强的自我监督图形卷积和多头注意力融合用于草药推.

Xianlun Tang1, Yuze Tang1, Xinran Liu1

  • 1Chongqing Key Laboratory of Complex Systems and Autonomous Control, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.

Artificial intelligence in medicine
|April 1, 2025
PubMed
概括

一种新的方法通过使用先进的人工智能来改进传统中国草药建议. 这种方法增强了草本特征表示和处方相关性,从而为自然疗法提供了更准确的建议.

关键词:
草药推建议 草药推多头注意力注意力多头注意力代表性的学习学习.自主监督的图形卷积.语义增强 语义增强 语义增强

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科学领域:

  • 整合和补充医学是整合和补充医学.
  • 医疗保健中的人工智能
  • 药理学 药理学是指药理学的学科.

背景情况:

  • 中国传统医学 (TCM) 是一种公认的自然疗法.
  • 草药推系统对于TCM应用至关重要,但面临着挑战.
  • 现有的系统存在数据稀疏性和对症状和草本特征的表现不佳的问题.

研究的目的:

  • 为了引入一种新的草药推方法,BSGAM.
  • 为了解决现有的TCM推系统的局限性.
  • 提高草药建议的准确性和有效性.

主要方法:

  • 使用BERT进行有效的实体嵌入.
  • 采用剩余图形卷积网络和自我监督学习来优化功能.
  • 整合一个多头注意力机制,用于特征融合和推.

主要成果:

  • 与基线方法相比,BSGAM显示出了显著的改进.
  • 在F1-Score@5,7.46%在F1-Score@10和6.60%在F1-Score@20中实现了6.80%的增加.
  • 在公共TCM处方数据集上验证的有效性.

结论:

  • BSGAM方法有效地提高了草药推的准确性.
  • 语义上增强的自我监督图形卷积和多头注意力融合对TCM有希望.
  • 这种方法为个性化草药推提供了更强大的解决方案.