O'Connor M J, Tu S W, Musen M A
Stanford Medical Informatics, Stanford University School of Medicine, Stanford, CA 94305-5479, USA.
Proc AMIA Symp. 2000:615-9.
Temporal indeterminancy is common in clinical medicine because the time of many clinical events is frequently not precisely known. Decision support systems that reason with clinical data may need to deal with this indeterminancy. This indeterminacy support must have a sound foundational model so that other system components may take advantage of it. In particular, it should operate in concert with temporal abstraction, a feature that is crucial in several clinical decision support systems that our group has developed. We have implemented a temporal query system called Tzolkin that provides extensive support for the temporal indeterminancies found in clinical medicine, and have integrated this support with our temporal abstraction mechanism. The resulting system provides a simple, yet powerful approach for dealing with temporal indeterminancy and temporal abstraction.
时间不确定性在临床医学中很常见,因为许多临床事件的时间常常无法精确得知。基于临床数据进行推理的决策支持系统可能需要应对这种不确定性。这种不确定性支持必须有一个合理的基础模型,以便其他系统组件能够加以利用。特别是,它应该与时间抽象协同运作,时间抽象是我们团队开发的几个临床决策支持系统中的一项关键特性。我们已经实现了一个名为Tzolkin的时间查询系统,该系统为临床医学中发现的时间不确定性提供了广泛支持,并已将这种支持与我们的时间抽象机制相结合。由此产生的系统为处理时间不确定性和时间抽象提供了一种简单而强大的方法。