临床研究中的数据驱动假设生成:我们从人类受试者研究中学到什么?
Xia Jing1, James J Cimino2, Vimla L Patel3
1Department of Public Health Sciences, College of Behavioral, Social and Health Sciences, Clemson University, Clemson, SC.
概括
产生有影响力的假设对于临床研究至关重要. 视觉分析工具 (VIADS) 可以加快假设生成,但可能会降低可行性评级,突出进一步研究的需要.
科学领域:
- 认知科学 认知科学
- 生物医学研究生物医学研究
- 临床研究 临床研究
背景情况:
- 假设生成是临床研究中一个关键的,但不太了解的早期步骤.
- 没有具有影响力的假设,研究的意义是可疑的,无论研究的严格程度如何.
- 现有的文献显示了科学思维的进步,但缺乏关于临床假设生成的原始研究.
研究的目的:
- 在临床研究人员中探索数据驱动假设生成的认知过程.
- 评估视觉交互分析工具 (VIADS) 对假设生成效率和质量的影响.
主要方法:
- 关于科学思维,推理和基于文献的发现的文学评论.
- 人类参与者研究,使用模拟环境来探索假设生成.
- 使用VIADS,这是一个用于过,总结和可视化大型健康数据集的工具.
主要成果:
- VIADS缩短了产生假设所需的平均时间和认知事件.
- 使用VIADS生成的假设获得了明显较低的可行性评级.
- 证实了人类参与者研究的可行性,以调查临床假设的产生.
结论:
- 视觉分析工具可以提高临床研究中假设生成的效率.
- 需要进一步开发工具,以平衡效率与生成假设的可行性.
- 支持需要进行更大规模的研究,以提高临床研究的生产力.
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