Burnside E, Rubin D, Shachter R
Stanford Medical Informatics, Stanford University, Stanford, CA, USA.
Proc AMIA Symp. 2000:106-10.
The interpretation of a mammogram and decisions based on it involve reasoning and management of uncertainty. The wide variation of training and practice among radiologists results in significant variability in screening performance with attendant cost and efficacy consequences. We have created a Bayesian belief network to integrate the findings on a mammogram, based on the standardized lexicon developed for mammography, the Breast Imaging Reporting And Data System (BI-RADS). Our goal in creating this network is to explore the probabilistic underpinnings of this lexicon as well as standardize mammographic decision-making to the level of expert knowledge.
乳房X光检查结果的解读以及基于该结果所做的决策涉及到不确定性的推理和管理。放射科医生在培训和实践方面存在很大差异，这导致筛查表现存在显著差异，并随之产生成本和疗效方面的后果。我们基于为乳房X光检查开发的标准化词汇表——乳腺影像报告和数据系统（BI-RADS），创建了一个贝叶斯信念网络，以整合乳房X光检查的结果。我们创建这个网络的目的是探索该词汇表的概率基础，并将乳房X光检查决策制定标准化到专家知识水平。
