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Interpretation of laboratory examination results and their simple representation

机译:解释实验室检查结果及其简单代表性

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Knowledge about the causal relationship between diseases and their laboratory findings is a key component for clinical decision support systems. For efficient acquisition of such knowledge, this paper attempted to represent the interpretation of laboratory results in a guidebook for laboratory examinations. A preliminary survey revealed the structure of the knowledge compiled in the guidebook, and found essential patterns in the cause-effect relationship. We then attempted to code the knowledge, utilizing a simple cause-effect relationship between exam results and their possible causes, expressed in a disease master table. For coding of the knowledge, a two-step approach was used: first the causing disease was looked up automatically in the disease master table, and then, manually. In the study, 84.5% of the knowledge in the guidebook was identified as a candidate for the coding in the simple cause-effect relationship, and 69.1% of the knowledge was successfully coded. Failure analysis suggested that further expressive power in the representation is gained only at the cost of considerable human intervention in the knowledge acquisition, and the cost for the utilization of the resulting data. Accordingly, for a certain type of application, which might prefer simplicity over accuracy or completeness of the information, the minimalist representation could be a reasonable choice.
机译:关于疾病与其实验室发现的因果关系的知识是临床决策支持系统的关键组成部分。为了有效地收购此类知识,本文试图代表实验室结果在实验室检查指南中的解释。初步调查显示了在指南中编制的知识结构,并发现原因效应关系中的基本模式。然后,我们试图通过考试结果和可能原因之间的简单原因关系来编写知识,在疾病大师表中表达。为了编码知识,使用两步方法:首先,在疾病主桌中自动抬起导致疾病,然后手动。在该研究中,指南中的84.5%的知识被确定为编码在简单的原因关系中的候选者,69.1%的知识已成功编码。失败分析表明,代表中的进一步表达能力仅以知识获取的相当大的人力干预成本,以及利用所得数据的成本。因此,对于某种类型的应用,这可能更倾向于通过信息的准确性或完整性的简单性,但极简主义表示可能是合理的选择。

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