直接高阶模糊规则分类系统在死亡率预测中的应用

A. D. Torshizi, L. Petzold, M. Cohen
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引用次数: 3

摘要

在美国,创伤是导致死亡的主要原因之一,在所有年龄组的死亡原因中排名第三。本文提出了一种基于一般2型模糊集概念的基于模糊规则的创伤患者死亡率预测方法。在这种方法中,规则库中的每个规则都有一个中频部分和一个THEN部分,中频部分的参数(先决条件)使用强大的通用2型模糊聚类算法自动提取,使模型能够处理噪声和/或缺失数据。为了验证所提出模型的有效性,在几个公开可用的数据集上实现了该模型。最后,基于大型临床数据集,将其用于预测创伤性损伤患者的死亡率。准确度结果表明,与文献中的清晰和模糊分类方法相比,所提出的方法具有优越的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Direct higher order fuzzy rule-based classification system: Application in mortality prediction
Trauma is one of the leading causes of death in the U.S. and is ranked third among death causes across all age groups. This paper presents a novel fuzzy rule-based classification approach based on the concept of General Type-2 Fuzzy sets to predict mortality for trauma patients. In this approach each rule in the rule-base has an IF and a THEN part and parameters of the IF part (antecedents) are automatically extracted using powerful general type-2 fuzzy clustering algorithms which enables the model to deal with noisy and/or missing data. To verify efficacy of the proposed model, it has been implemented on several publicly available datasets. Finally, it is used to predict mortality among patients having traumatic injuries based on a large clinical dataset. Accuracy results demonstrate superior capabilities of the proposed approach compared to crisp and fuzzy classification methods in the literature.
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