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运用知识维护进行偏好评估。

Using knowledge maintenance for preference assessment.

作者信息

Jain N L, Kahn M G

机构信息

Department of Internal Medicine; Washington University, St. Louis, Missouri, USA.

出版信息

Proc Annu Symp Comput Appl Med Care. 1995:263-9.

Abstract

Most real-life decisions require the decision maker to make trade-offs in order to fulfill multiple conflicting objectives. This is especially true in medical decision making while selecting the optimal therapy plan from among competing therapy plans for a patient. Multi-attribute utility theory provides a framework to specify these trade-offs for optimal decision making based on the preferences of the decision maker. However traditional preference-assessment techniques are difficult to implement and rarely elicit the true preferences of the decision maker. We describe a new preference-assessment method based on the concept of knowledge maintenance where the preference model is changed each time it makes an incorrect recommendation. The method is implemented in a decision-theoretic system to evaluate competing three-dimensional radiation treatment plans. The preference-assessment method leads to preference models which perform better than preference models elicited using traditional assessment techniques.

摘要

大多数现实生活中的决策都要求决策者进行权衡,以实现多个相互冲突的目标。在医疗决策中,从针对患者的多种相互竞争的治疗方案中选择最优治疗方案时尤其如此。多属性效用理论提供了一个框架,用于根据决策者的偏好来确定这些权衡,以进行最优决策。然而,传统的偏好评估技术难以实施,而且很少能引出决策者的真实偏好。我们描述了一种基于知识维护概念的新的偏好评估方法,即每次偏好模型给出错误推荐时,就对其进行更改。该方法在一个决策理论系统中实现,用于评估相互竞争的三维放射治疗方案。这种偏好评估方法所产生的偏好模型,其性能优于使用传统评估技术得出的偏好模型。

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本文引用的文献

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