A fuzzy cognitive map based tool for prediction of infectious diseases

E. Papageorgiou, Nikolaos I. Papandrianos, G. Karagianni, G. Kyriazopoulos, D. Sfyras
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引用次数: 63

Abstract

The prediction of pulmonary infections in intensive care unit is a complex medical task where a large number of parameters, tests, clinical symptoms and laboratory results are present. The knowledge of physicians according to the physical examination and clinical measurements are the main point to succeed a diagnosis and monitoring patient status. This paper presents the results of our investigation of the problem of representing knowledge for medical diagnosis systems concentrated on the pulmonary infections. The main topic of the presented effort is the representation of the cause-effect relationships within medical data by the application of the soft computing technique of fuzzy cognitive maps. The fuzzy cognitive map is a knowledge based technique for modeling and representing experts' knowledge. It can handle efficiently with complex modeling problems to assess medical decision making tasks. Due to its easy graphical representation the proposed FCM can be used to make the medical knowledge widely available through computer consultation systems.
基于模糊认知地图的传染病预测工具
重症监护病房肺部感染的预测是一项复杂的医疗任务,涉及大量参数、检查、临床症状和实验室结果。医生根据体格检查和临床测量掌握的知识是成功诊断和监测患者病情的要点。本文介绍了我们对集中于肺部感染的医学诊断系统的知识表示问题的研究结果。本文的主要课题是应用模糊认知图的软计算技术来表示医学数据中的因果关系。模糊认知地图是一种基于知识的专家知识建模和表示技术。它可以有效地处理复杂的建模问题,以评估医疗决策任务。由于其易于图形化表示,所提出的FCM可用于通过计算机会诊系统广泛获取医学知识。
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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