在数据驱动的医学研究中早期的多式数据集成 - - 范围审查
Julia Gehrmann1, Oya Beyan1,2
1Institute for Biomedical Informatics, University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany.
Studies in health technology and informatics
|September 5, 2024
概括
本研究回顾了数据驱动医学研究 (DDMR) 的早期多式联络数据集成 (MMDI) 方法. 它对21种方法进行了分类,强调了在复杂的医疗数据分析中选择最佳集成管道的关键特征.
科学领域:
- 医疗信息学 医疗信息学
- 在医疗保健中的数据科学.
- 计算生物学 计算生物学
背景情况:
- 数据驱动医学研究 (DDMR) 需要多模式数据 (MMD) 来捕捉临床复杂性.
- 早期的多式联络数据集成 (MMDI) 方法,在分析之前进行,从简单的连接到深度学习.
- 晚期MMDI在结合结果之前单独分析模式.
研究的目的:
- 系统地审查和分析早期多式联运数据集成 (MMDI) 的方法.
- 将早期的MMDI方法分类,并对DDMR项目的特征进行总结.
- 在医学研究中为选择最佳的MMDI策略提供信息.
主要方法:
- 根据PRISMA指南进行了范围审查.
- 分析了2019年至2024年间发表的21篇关于早期MMDI的评论.
- 将已识别的MMDI方法分为四个不同的组.
主要成果:
- 早期的MMDI方法被分为四大类.
- 总结了每个类别的关键特征,以指导方法选择.
- 早期的MMDI通常涉及顺序管道执行,通常需要手动优化.
结论:
- 选择早期的MMDI方法取决于研究背景,数据复杂性和团队专业知识.
- 未来的研究应该比较早期与晚期的MMDI,并自动化管道优化.
- 有效的MMDI对于整体的DDMR和整合现实世界医疗数据至关重要.
更多相关视频
07:13Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
Published on: October 27, 2023
1.1K
08:51Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts
Published on: September 20, 2024
1.2K
相关概念视频
Data Validation
Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...
Nursing assessment guides are generally based on holistic models rather than medical...
Data Validation
Method validation is a crucial process in analytical chemistry designed to confirm that a given method consistently produces reliable and high-quality results. This process is essential when a method is applied to different sample matrices or when procedural modifications are made, ensuring that the results meet acceptable standards across various applications.
Key parameters for method validation include:
Key parameters for method validation include:
Statistical Methods for Analyzing Epidemiological Data
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
Statistical Software for Data Analysis and Clinical Trials
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
