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相关概念视频

Data Collection by Observations01:08

Data Collection by Observations

12.1K
Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the most widely used methods of data collection. It involves collecting data by observing the behavior and physical characteristics of a sample without making any modifications to the sample.
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
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Data Collection III01:05

Data Collection III

2.8K
The physical assessment examines the patient for objective data that defines the patient's condition, and aids in formulating the nursing care plan. The purpose of physical assessment is a health status appraisal, which includes identifying health problems, and establishing a database for nursing intervention.
The principles to begin the physical assessment include conducting a comprehensive or problem-related history in a quiet, well-lit room, emphasizing privacy and comfort for the...
2.8K
Data Collection by Survey01:07

Data Collection by Survey

6.5K
The systematic method of obtaining and analyzing accurate information of a population is called data collection. A survey is a standard method of data collection that involves collecting information from a target human population about their experience, opinion, or knowledge of a product, service, or process. The responses are recorded and interpreted. The most common survey examples are written questionnaires, face-to-face or telephonic conversations, focus groups, and electronic (e-mail or...
6.5K
Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

300
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
300
Mass Analyzers: Common Types01:19

Mass Analyzers: Common Types

656
The quadrupole mass analyzer consists of four cylindrical metal rods arranged in a diamond carrying a DC voltage and a radio-frequency AC voltage. The motion of ions through the quadrupole depends on the field strength, causing only ions of a certain m/z to resonate successfully and strike the detector at a given field strength. Though the transmission rate for these analyzers is high, the exact elemental composition of the sample is not determined because of low resolution; however, they are...
656
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

65
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...
65

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Updated: Jul 24, 2025

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies
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从共享的研究数据中学习重要的共同数据元素:我们所有人计划分析分析.

Craig S Mayer1, Vojtech Huser1

  • 1Lister Hill National Center for Biomedical Communication, National Library of Medicine, NIH, Bethesda, Maryland, United States of America.

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概括
此摘要是机器生成的。

我们所有人计划使用共同数据元素 (CDE) 和OMOP共同数据模型来标准化临床研究数据. 这种整合有助于分析和监测健康和生活方式的变化.

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Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies
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Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
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科学领域:

  • 医疗信息学 医疗信息学
  • 临床数据管理 临床数据管理
  • 生物医学研究生物医学研究

背景情况:

  • 在人类临床研究中协调数据收集对于强大的研究至关重要.
  • 像我们所有人 (AoU) 计划这样的大规模举措旨在使用共同数据元素 (CDEs) 标准化数据.
  • 为了标准化研究和现实世界的数据,越来越多地采用了OMOP共同数据模型.

研究的目的:

  • 分析我们所有人 (AoU) 计划中的数据标准化方法.
  • 评估AoU中使用的共同数据元素 (CDE) 和唯一数据元素 (UDE) 的程度.
  • 通过使用OMOP共同数据模型评估研究和电子健康记录数据的整合.

主要方法:

  • 从已建立的术语 (LOINC,SNOMED CT) 中定义的元素作为CDE.
  • 在参与者提供的信息 (PPI) 中定义的自定义概念作为 UDEs.
  • 在研究案例报告表 (CRF) 和数据上下文中分析了元素和价值分布.

主要成果:

  • AoU使用了1033个研究元素,其中大多数是UDEs (84.1%).
  • LOINC和SNOMED CT是CDE的主要来源,许多LOINCCDE源自之前的倡议 (例如PhenX,PROMIS).
  • OMOP模型为64个元素促进了研究和日常医疗保健数据的整合,使健康和生活方式的监测成为可能.

结论:

  • 我们所有人计划有效地使用OMOP共同数据模型进行数据标准化和集成.
  • 在AoU等大型研究中增加了CDE的使用,提高了数据可比性和分析效率.
  • 标准化数据收集提高了理解和分析临床研究数据的方便性,减少了与研究特定格式相关的挑战.