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一种结合时间抽象和基于案例推理的时间进程预后模型。

A prognostic model for temporal courses that combines temporal abstraction and case-based reasoning.

作者信息

Schmidt Rainer, Gierl Lothar

机构信息

Institut für Medizinische Informatik und Biometrie, Universität Rostock, Rembrandtstr. 16/17, D-18055 Rostock, Germany.

出版信息

Int J Med Inform. 2005 Mar;74(2-4):307-15. doi: 10.1016/j.ijmedinf.2004.03.007.

Abstract

Since clinical management of patients and clinical research are essentially time-oriented endeavours, reasoning about time has become a hot topic in medical informatics. Here we present a method for prognosis of temporal courses, which combines temporal abstractions with case-based reasoning. It is useful for application domains where neither well-known standards, nor known periodicity, nor a complete domain theory exist. We have used our method in two prognostic applications. The first one deals with prognosis of the kidney function for intensive care patients. The idea is to elicit impairments on time, especially to warn against threatening kidney failures. Our second application deals with a completely different domain, namely geographical medicine. Its intention is to compute early warnings against approaching infectious diseases, which are characterised by irregular cyclic occurrences. So far, we have applied our program on influenza and bronchitis. In this paper, we focus on influenza forecast and show first experimental results.

摘要

由于对患者的临床管理和临床研究本质上都是以时间为导向的工作,因此关于时间的推理已成为医学信息学中的一个热门话题。在此,我们提出一种用于时间进程预后的方法,该方法将时间抽象与基于案例的推理相结合。它适用于既没有知名标准、也没有已知周期性、也不存在完整领域理论的应用领域。我们已将我们的方法应用于两个预后应用中。第一个应用涉及重症监护患者的肾功能预后。其思路是及时发现损伤,尤其是警告即将发生的肾衰竭。我们的第二个应用涉及一个完全不同的领域,即地理医学。其目的是计算针对即将到来的传染病的早期预警,这些传染病的特点是发生周期不规则。到目前为止,我们已将我们的程序应用于流感和支气管炎。在本文中,我们专注于流感预测并展示了初步的实验结果。

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