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一种在计算机化医疗领域中对决策过程进行量化的方法。

A method for the quantification of the decision-making process in a computer-oriented medical world.

作者信息

Cerutti S, Timó Pieri C

出版信息

Int J Biomed Comput. 1981 Jan;12(1):29-57. doi: 10.1016/0020-7101(81)90024-6.

Abstract

The aim of this paper is to suggest an original approach to the decision-making process in a computer-oriented medical record, now in use on an experimental basis, at a major District Hospital in Sesto S. Giovanni, near Milano, in a general medicine department. Two types of algorithms are introduced in order to 'capture' more effectively the different steps of the decisional process on the basis of a differential diagnosis approach. The first refers to the field of symbolic reasoning, close to the area of Artificial Intelligence and uses score variables, while the other can handle qualitative expressions since it follows the fuzzy-set approach. A comparison among the performances offered by such algorithms, the physician's decision and the Bayes Rule is then carried on. Further developments should clarify the problems of parameter sensitivity as regards the successive steps to the final diagnosis. The present implementation is suitable for individual hospital departments and educational purposes.

摘要

本文旨在提出一种针对以计算机为导向的病历决策过程的创新方法,该方法目前正在米兰附近的塞斯托圣乔瓦尼的一家大型地区医院的普通内科进行实验性应用。引入了两种算法,以便基于鉴别诊断方法更有效地“捕捉”决策过程的不同步骤。第一种算法涉及符号推理领域,与人工智能领域相近并使用评分变量,而另一种算法则采用模糊集方法,因此可以处理定性表达。然后对这些算法的性能、医生的决策和贝叶斯规则进行比较。进一步的发展应阐明关于最终诊断后续步骤的参数敏感性问题。目前的实施方案适用于个别医院科室和教育目的。

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