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将基于案例的推理与电子病历系统相结合。

Integrating case-based reasoning with an electronic patient record system.

机构信息

School of Computing, The Robert Gordon University, Aberdeen, Scotland, UK.

出版信息

Artif Intell Med. 2011 Feb;51(2):117-23. doi: 10.1016/j.artmed.2010.12.004. Epub 2011 Jan 12.

Abstract

UNLABELLED

Electronic patient records (EPRs) contain a wealth of patient-related data and capture clinical problem-solving experiences and decisions. Excelicare is such a system which is also a platform for the national generic clinical system in the UK.

OBJECTIVE

This paper presents, ExcelicareCBR, a case-based reasoning (CBR) system which has been developed to complement Excelicare. Objective of this work is to integrate CBR to support clinical decision making by harnessing electronic patient records for clinical experience reuse.

METHODS

CBR is a proven problem solving methodology in which past solutions are reused to solve new problems. A key challenge that we address in this paper is how to extract and represent a case from an EPR. Using an example from the lung cancer domain we demonstrate our generic case representation approach where Excelicare fields are mapped to case features. Once the case base is populated with cases containing data from the EPRs database a standard weighted k-nearest neighbour algorithm combined with a genetic algorithm based feature weighting mechanism is used for case retrieval and reuse.

CONCLUSIONS

We conclude that incorporating case authoring functionality and a generic retrieval mechanism were key to successful integration of ExcelicareCBR. This paper also demonstrates how the application of CBR can enable sharing of lessons learned through the retrieval and reuse of EPRs captured as cases in a case base.

摘要

未加标签

电子病历(EPR)包含大量与患者相关的数据,并记录临床解决问题的经验和决策。Excelicare 就是这样一个系统,它也是英国国家通用临床系统的一个平台。

目的

本文提出了 ExcelicareCBR,这是一个基于案例的推理(CBR)系统,旨在补充 Excelicare。这项工作的目的是通过利用电子病历来支持临床经验的重复使用,将 CBR 集成到临床决策支持中。

方法

CBR 是一种经过验证的问题解决方法,它通过重复使用过去的解决方案来解决新问题。我们在本文中解决的一个关键挑战是如何从 EPR 中提取和表示一个案例。我们使用肺癌领域的一个示例演示了我们的通用案例表示方法,其中 Excelicare 字段被映射到案例特征。一旦用来自 EPR 数据库的数据填充了案例库,就可以使用标准加权 k-最近邻算法结合基于遗传算法的特征加权机制进行案例检索和重用。

结论

我们得出结论,纳入案例创作功能和通用检索机制是成功集成 ExcelicareCBR 的关键。本文还演示了如何通过检索和重用作为案例库中案例捕获的 EPR,应用 CBR 来实现经验教训的共享。

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