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Computing with words and machine learning in medical diagnostics

机译:医学诊断中的单词计算和机器学习

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The paper deals with the mathematical simulation of empirical learning in medical diagnostics. Such a simulation essentially amounts to solving both the problem of how to acquire, represent, and objectify the smallest typical units of diagnostic knowledge and the problem of how to identify the subject-specific situations in which diagnostic learning may take place at all. A solution to the first question will be provided by using so called fuzzy probabilities as a model. The second problem is solved by adequately formalizing that kind of knowledge as it is found in standard sources like textbooks for instance. (C) 2001 Elsevier Science Inc. All rights reserved. [References: 6]
机译:本文涉及医学诊断中经验学习的数学模拟。这样的模拟本质上等于解决了如何获取,表示和客观化诊断知识的最小典型单位的问题,以及如何识别可能发生诊断学习的特定对象情况的问题。将通过使用所谓的模糊概率作为模型来提供第一个问题的解决方案。第二个问题是通过适当形式化这种知识来解决的,例如在教科书之类的标准资源中就可以找到这种知识。 (C)2001 Elsevier Science Inc.保留所有权利。 [参考:6]

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