相关实验视频
Updated: Jan 13, 2026

10:56
A User-friendly and Powerful R Analysis of Large-scale Datasets
Published on: November 4, 2025
332
超越数据集:将公众的声音融入数据科学中
Ana-Paula Rubio1, Janette Dunn2, Janice Borthwick2
1Centre for Medical Informatics, University of Edinburgh, Edinburgh, UK. arubio@ed.ac.uk.
Research involvement and engagement
|January 8, 2026
概括
患者和公众参与和参与 (PPIE) 对健康研究质量至关重要. 这篇文章反映了在像SCONe这样的大规模数据科学研究联盟中实施PPIE的挑战.
科学领域:
- 眼科医生 眼科 眼科
- 数字健康数字健康
- 健康 数据科学 数据科学
背景情况:
- 医疗数据的数字化支持诸如苏格兰合作光学-眼科网络eResearch (SCONe) 等倡议.
- 患者和公众参与和参与 (PPIE) 对于提高健康研究质量,相关性和可接受性至关重要.
- 在PPIE实施方面仍然存在挑战,包括不一致的术语和缺乏指导,特别是在数据科学方面.
研究的目的:
- 提供一个反映的对挑战和SCONe在制定PPIE战略所面临的障碍的帐户.
- 为大规模研究联盟中实施PPIE提供见解.
- 为数据科学研究的公私伙伴关系中未来的举措提供实际指导.
主要方法:
- 对SCONe倡议的PPIE战略开发进行反思.
- 分析过程中遇到的挑战和障碍.
- 对大规模数据科学研究的洞察力进行文件化.
主要成果:
- 在大型研究联盟中实施PPIE面临重大挑战.
- 数据科学中PPIE报告不足阻碍了框架的开发.
- SCONe的经验凸显了建立有意义的公共伙伴关系的复杂性.
结论:
- 有意义的PPIE实施需要解决大规模数据科学研究中的特定挑战.
- 记录SCONe这样的经验对于开发有效的PPIE框架至关重要.
- 需要实用指导来增强公众参与健康数据科学的影响和相关性.
相关概念视频
Data Collection by Observations
14.5K
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...
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...
14.5K
Data Collection by Experiments
27.0K
Data collection is a systematic method of obtaining, observing, measuring, and analyzing accurate information. An experimental study is a standard method of data collection that involves the manipulation of the samples by applying some form of treatment prior to data collection. It refers to manipulating one variable to determine its changes on another variable. The sample subjected to treatment is known as “experimental units.”
An example of the experimental method is a public...
An example of the experimental method is a public...
27.0K
Data Reporting and Recording
5.3K
Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...
5.3K
Data Collection I
7.8K
Data collection gathers information needed to make accurate judgments about a patient's present condition. During a health history interview, subjective data is collected from the patient, their caregivers, or family members, and objective data is collected through observations and physical assessment. Patients are the primary source of subjective data. Thus information gathered from patients through interviews, observations, and physical examination is primary data. Secondary sources of...
7.8K
Introduction to Statistics
61.6K
The science of statistics involves collecting, analyzing, interpreting, and presenting data. The method of collecting, organizing, and summarizing data is called descriptive statistics. The systematic method of drawing inferences from the sample data and predicting unknown characteristics of a population is called inferential statistics.
In statistics, the collection of individuals or objects under study is called population. The idea of sampling is to select a portion of the larger population...
In statistics, the collection of individuals or objects under study is called population. The idea of sampling is to select a portion of the larger population...
61.6K
Statistical Analysis: Overview
14.1K
When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
14.1K

