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相关概念视频

Uncertainty: Overview00:59

Uncertainty: Overview

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In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
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Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
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Propagation of Uncertainty from Random Error

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An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
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Biostatistics plays a crucial role in understanding and analyzing data in healthcare and biology. Biostatisticians conduct experiments, gather evidence, and draw meaningful conclusions using statistical methods and techniques. Different variables form the foundation of biostatistical analysis, allowing researchers to understand and interpret data effectively. These variables are classified into different types, each serving a specific purpose in statistical analysis.
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Genomics02:02

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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
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相关实验视频

Updated: Jun 7, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
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迈向量化,建模和探索生物医学知识图中的不确定性的一步.

Adil Bahaj1, Mounir Ghogho2

  • 1International University of Rabat, TICLab, Sala el Jadida 11103, Morocco.

Computers in biology and medicine
|November 14, 2024
PubMed
概括

这项研究使用对文本证据的深度学习来量化生物医学知识图 (BKG) 的不确定性. 开发的方法KGB2U允许自动评估不确定性,并从大型BKG中发现知识.

关键词:
生物医学知识图表.知识图嵌入知识图.精准医学是一门精准的医学.不确定知识图表 不确定知识图表

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科学领域:

  • 生物医学信息学 生物医学信息学
  • 人工智能的人工智能
  • 知识表示 知识表示

背景情况:

  • 生物医学知识图 (BKG) 对于组织复杂的生物数据至关重要.
  • 在BKG中量化事实不确定性对于可靠的数据解释至关重要.
  • 现有的方法通常依赖于手动功能工程,限制了可扩展性和准确性.

研究的目的:

  • 开发一种深度学习方法,用于自动量化和建模BKG中的不确定性.
  • 利用文本支持证据来评估BKG条目的事实性和信心分数.
  • 为了使知识发现,并从不确定的BKG数据识别新的见解.

主要方法:

  • 使用句子转换器从辅助句子中提取深度特征.
  • 使用一个天真的贝叶斯分类器来确定句子的事实性.
  • 通过平均句子事实性得分来量化事实不确定性,产生0到1之间的信心值.

主要成果:

  • 深度学习模型显著优于使用手工制作的功能的传统方法.
  • 证明了处理大规模BKG的能力,从SemMedDB创建了一个新的不确定的BKG数据集 (USemMedDB).
  • 展示了 BKG 结构和信心评分之间的相关性,以及该模型预测新事实信心的能力.

结论:

  • 文本证据可以有效地用于自动量化BKG事实中的不确定性.
  • 开发的不确定的BKG促进知识发现和识别新的科学见解.
  • 该KGB2U工具可用于处理和分析大型生物医学知识图.