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Evaluating the decision accuracy and speed of clinical data visualizations

机译:评估临床数据可视化的决策准确性和速度

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摘要

Clinicians face an increasing volume of biomedical data. Assessing the efficacy of systems that enable accurate and timely clinical decision making merits corresponding attention. This paper discusses the multiple-reader multiple-case (MRMC) experimental design and linear mixed models as means of assessing and comparing decision accuracy and latency (time) for decision tasks in which clinician readers must interpret visual displays of data. These tools can assess and compare decision accuracy and latency (time). These experimental and statistical techniques, used extensively in radiology imaging studies, offer a number of practical and analytic advantages over more traditional quantitative methods such as percent-correct measurements and ANOVAs, and are recommended for their statistical efficiency and generalizability. An example analysis using readily available, free, and commercial statistical software is provided as an appendix. While these techniques are not appropriate for all evaluation questions, they can provide a valuable addition to the evaluative toolkit of medical informatics research.
机译:临床医生面临着越来越多的生物医学数据。评估能够准确,及时地进行临床决策的系统的有效性值得相应的关注。本文讨论了多阅读器多案例(MRMC)实验设计和线性混合模型,作为评估和比较决策任务的决策准确性和等待时间(时间)的方法,临床医生必须在其中解释数据的视觉显示。这些工具可以评估和比较决策的准确性和延迟(时间)。这些实验和统计技术已广泛用于放射成像研究中,与更传统的定量方法(如百分比校正测量和方差分析)相比,具有许多实用和分析优势,并建议其统计效率和可推广性。附录中提供了使用现成的,免费的和商业的统计软件进行的示例分析。尽管这些技术并不适合所有评估问题,但它们可以为医学信息学研究评估工具包提供有价值的补充。

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