基于遗传算法的嗜中性认知图谱医学诊断混合模型

Gaurav, Megha Kumar, Kanika Bhutani, Swati Aggarwal
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引用次数: 41

摘要

本文提出了两种软计算技术的组合:中性认知图和遗传算法,用于医学疾病诊断的建模。在此之前,许多研究者提出了基于认知图谱和遗传算法的医疗决策支持系统。采用模糊认知地图与遗传算法的混合模型来处理决策不明确的情况。在现实世界数据并不总是一致的情况下,作者提出了一种新的中性认知地图与遗传算法的混合模型来处理不确定性。该模型将为医疗决策支持系统提供清晰的疾病诊断。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hybrid model for medical diagnosis using Neutrosophic Cognitive Maps with Genetic Algorithms
This paper presents a combination of two soft computing techniques: Neutrosophic cognitive maps and Genetic algorithm for modeling of medical disease diagnosis. Earlier, medical decision support system was proposed by many researchers where cognitive maps along with genetic algorithm were experimented. The hybrid model of fuzzy cognitive maps with genetic algorithm was implemented to handle situations where decisions are not clearly distinct. In real world situation data is not always consistent so, authors proposed a new hybrid model of Neutrosophic Cognitive Maps with Genetic Algorithms to handle indeterminacy. The proposed model will provide distinct diagnosis of disease in medical decision support system.
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