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Author Spotlight: Automated Deep Brain Stimulation for Parkinson's Disease - Exploring the Possibilities and Challenges of Home Monitoring
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数据和流程协调多国,多地点研究数据.

Jonathan Turner1,2, Sinéad Impey1, Frances Gibbons1

  • 1ADAPT Centre, Trinity College Dublin, Dublin, Ireland.

Studies in health technology and informatics
|August 23, 2024
PubMed
概括

在多个地点协调数据收集流程对于创建统一的研究数据集至关重要. 本研究详细介绍了多国精密ALS项目的流程调整方面的挑战.

关键词:
肌缩侧面硬化症 (Amyotrophic Lateral Sclerosis) 是一种肌缩侧面硬化症.统一化 统一化 统一化过程调整对齐的过程.

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科学领域:

  • 神经科学是一个神经科学.
  • 数据科学数据科学数据科学
  • 临床研究 临床研究

背景情况:

  • 多个地点的研究需要统一的数据进行准确的分析.
  • 语义整合和标准化收集单元本身是不够的.
  • 数据收集过程的调整是一个关键的,经常被忽视的因素.

研究的目的:

  • 识别和描述多地点研究数据收集中的协调挑战.
  • 专注于跨国项目的流程调整问题.
  • 为未来的协作研究数据倡议提供最佳实践信息.

主要方法:

  • 精密ALS项目的数据收集程序的定性分析.
  • 识别跨国际站点数据处理中的差异.
  • 案例研究方法侧重于过程调整挑战.

主要成果:

  • 在协调不同国家站点的数据收集流程方面发现了重大挑战.
  • 当地协议和基础设施的变化阻碍了完全协调.
  • 记录了过程错位的具体例子,影响了数据统一性.

结论:

  • 为了实现完全协调的研究数据集,需要严格调整数据收集过程.
  • 流程协调是多站点研究中数据质量和分析有效性的关键决定因素.
  • 积极应对这些挑战对于成功的国际研究合作至关重要,如精密ALS.