Fuzzy sets in modeling patient’s disease states in medical diagnostics support algorithms

Andrzej Ameljańczyk, Tomasz Ameljańczyk
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Abstract

The article presents the concept of using fuzzy sets methodology in modelling patientʼs disease states for preliminary medical diagnosis. The preliminary medical diagnosis is based on the identified disease symptoms. The basis of the algorithm are descriptions of the patientʼs disease status and patterns of disease entities. These patterns were defined as fuzzy sets. The paper presents simple classifiers that allow he a preliminary diagnosis based on the analysis of fuzzy sets for the use of the general practitioner.
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医学诊断支持算法中的病人疾病状态建模模糊集
文章介绍了使用模糊集方法模拟病人疾病状态进行初步医疗诊断的概念。初步医疗诊断基于已确定的疾病症状。该算法的基础是病人疾病状态的描述和疾病实体的模式。这些模式被定义为模糊集。本文介绍了一些简单的分类器,这些分类器可以在模糊集分析的基础上进行初步诊断,供全科医生使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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