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相关概念视频

Genome-wide Association Studies-GWAS01:11

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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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Electronic Medical Records (EMRs) primarily center around electronically documenting patients' health information within a single healthcare organization or practice. They contain essential clinical data related to a patient's medical history, diagnoses, medications, treatment plans, lab results, and other pertinent information relevant to the specific encounter or episode of care. EMRs are designed to streamline documentation and workflow processes within individual healthcare...
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Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

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Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
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The nurse documents nursing diagnoses and enters them into the patient record. The identified patient's nursing diagnosis is either written out with a plan of care or entered into the electronic health record.
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Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This...
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Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
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相关实验视频

Updated: Jun 21, 2025

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
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利用易出错的算法衍生的表型:加强对电子健康记录数据中的风险因素的关联研究.

Yiwen Lu1, Jiayi Tong2, Jessica Chubak3

  • 1Center for Health AI and Synthesis of Evidence (CHASE), Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; The Graduate Group in Applied Mathematics and Computational Science, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, USA.

Journal of biomedical informatics
|July 14, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新方法,将多个电子健康记录 (EHR) 现型结合起来,减少偏见并提高关联研究的效率. 该方法提高了统计准确性,并为表型/暴露分析提供了强大的替代方案.

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Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
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Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
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科学领域:

  • 生物医学信息学 生物医学信息学
  • 健康 数据科学 数据科学
  • 临床流行病学临床流行病学

背景情况:

  • 多个可计算的表型越来越多地来自电子健康记录 (EHR).
  • 基于EHR的关联研究通常使用单个表型,可能引入偏见.
  • 表型错误可能会影响基于EHR的研究的准确性和效率.

研究的目的:

  • 开发一种用于同时利用多个EHR衍生的表型的新方法.
  • 为了减少EHR数据中的表型错误引起的偏见.
  • 提高表型/暴露关联研究的效率和准确性.

主要方法:

  • 开发了一种将多个算法衍生的表型与验证的结果结合在一起的方法.
  • 该方法采用了统计学上高效的看似无关的回归框架.
  • 通过模拟研究和现实世界EHR数据分析 (结肠癌复发) 来评估性能.

主要成果:

  • 与单个表型方法相比,实现了实质性的偏差减少,特别是当没有单个表型均优越时.
  • 与仅使用一个算法衍生的表型相比,估计效率提高了多达30%.
  • 该方法在整合多种表型以提高统计准确度方面表现出有效性.

结论:

  • 拟议的方法有效地整合了来自EHR数据的多种表型.
  • 它提供了一个强大的替代单替代偏差校正方法.
  • 该方法提高了基于EHR的关联研究中的偏差减少,统计准确性和效率.