Quantitative Analysis of Uncertainty in Medical Reporting: Creating a Standardized and Objective Methodology
Quantitative Analysis of Uncertainty in Medical Reporting: Creating a Standardized and Objective Methodology
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医疗报告中不确定性的定量分析：创建标准化和客观的方法
DOI：
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发表时间：
2018
影响因子：
4.4
通讯作者：
B. Reiner
中科院分区：
文献类型：
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作者：
B. Reiner
长期以来，基于文本的医疗报告中的不确定性一直被认为是有问题的，经常导致误解和沟通错误。解决报告不确定性的负面临床影响的一个策略是创建一种标准化的方法来表征和量化不确定语言，这可以为报告作者和读者提供与所感知的诊断置信度和准确性水平相关的背景。在创建这种分析时可以采用许多计算机化的策略，包括字符串搜索、自然语言处理和理解、直方图分析、主题建模和机器学习。导出的不确定性数据提供了实时客观分析报告不确定性的可能性，并与结果分析相关联，以便在干预将具有最大临床影响的情况下，在护理点提供上下文和特定于用户的决策支持。
Uncertainty in text-based medical reports has long been recognized as problematic, frequently resulting in misunderstanding and miscommunication. One strategy for addressing the negative clinical ramifications of report uncertainty would be the creation of a standardized methodology for characterizing and quantifying uncertainty language, which could provide both the report author and reader with context related to the perceived level of diagnostic confidence and accuracy. A number of computerized strategies could be employed in the creation of this analysis including string search, natural language processing and understanding, histogram analysis, topic modeling, and machine learning. The derived uncertainty data offers the potential to objectively analyze report uncertainty in real time and correlate with outcomes analysis for the purpose of context and user-specific decision support at the point of care, where intervention would have the greatest clinical impact.
影响因子：
5.5
作者：
Cai, Tianrun;Giannopoulos, Andreas A.;Mitsouras, Dimitrios
通讯作者：
Mitsouras, Dimitrios