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首页> 外文期刊>Expert Systems with Application >Multi-stage modeling using fuzzy multi-criteria feature selection to improve survival prediction of ICU septic shock patients
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Multi-stage modeling using fuzzy multi-criteria feature selection to improve survival prediction of ICU septic shock patients

机译：使用模糊多准则特征选择的多阶段建模可改善ICU败血性休克患者的生存预测

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摘要

In many binary medical classification problems, the cost of misclassifying one category is higher than the other, and in these applications it is desirable to employ a classifier with selective sensitivity or specificity. This work explores the utility of a fuzzy multi-criteria function for performance evaluation during knowledge-based medical classification and prediction. The method presented here uses fuzzy optimization to combine the sensitivity, specificity, and accuracy of classification as goals in a single objective function. This approach is used to assign flexible goals, which can be used to maximize the outcome in terms of each one of the goals. The proposed approach significantly increases the sensitivity and the specificity while maintaining or increasing accuracy. The versatility of the method is further exploited in a multi-model approach, using individual structures of multi-objective optimization of sensitivity and specificity separately, and then combining their outcomes through a decision-making module. Among various medical benefits derived from applying this technique, the divergent feature sets selected by high sensitivity and specificity models lend insight into factors more integrally connected to what causes risk of death for patients.
机译：在许多二元医学分类问题中，将一类分类错误的成本高于另一种，在这些应用中，希望采用具有选择性敏感性或特异性的分类器。这项工作探索了模糊多准则函数在基于知识的医学分类和预测过程中用于绩效评估的效用。此处介绍的方法使用模糊优化将分类的敏感性，特异性和准确性作为目标组合在单个目标函数中。该方法用于分配灵活的目标，可用于根据每个目标最大化结果。所提出的方法显着提高了灵敏度和特异性，同时保持或提高了准确性。在多模型方法中进一步利用了该方法的多功能性，分别使用敏感性和特异性的多目标优化的各个结构，然后通过决策模块将其结果组合在一起。在应用该技术所获得的各种医学益处中，通过高灵敏度和特异性模型选择的不同特征集使人们对与导致患者死亡风险的原因更紧密相关的因素有了更深入的了解。

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  • 来源
    《Expert Systems with Application》 |2012年第16期|p.12332-12339|共8页
  • 作者

    Federico Cismondi; Abigail L. Horn; Andre S. Fialho; Susana M. Vieira; Shane R. Reti; Joao M.C. Sousa; Stan Finkelstein;

  • 作者单位

    Engineering Systems Division and MLT Portugal Program, Massachusetts institute of Technology, Cambridge, MA, USA,Dept. of Mechanical Engineering, CIS/IDMEC - LAETA, Instituto Superior Tecnico, Technical University of Lisbon, Lisbon, Portugal,Division of Clinical Informatics, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA USA, 77 Massachusetts Avenue, E40-221, 02139 Cambridge, MA, USA;

    Engineering Systems Division and MLT Portugal Program, Massachusetts institute of Technology, Cambridge, MA, USA,Dept. of Mechanical Engineering, CIS/IDMEC - LAETA, Instituto Superior Tecnico, Technical University of Lisbon, Lisbon, Portugal;

    Engineering Systems Division and MLT Portugal Program, Massachusetts institute of Technology, Cambridge, MA, USA,Dept. of Mechanical Engineering, CIS/IDMEC - LAETA, Instituto Superior Tecnico, Technical University of Lisbon, Lisbon, Portugal,Division of Clinical Informatics, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA USA;

    Dept. of Mechanical Engineering, CIS/IDMEC - LAETA, Instituto Superior Tecnico, Technical University of Lisbon, Lisbon, Portugal;

    Division of Clinical Informatics, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA USA;

    Dept. of Mechanical Engineering, CIS/IDMEC - LAETA, Instituto Superior Tecnico, Technical University of Lisbon, Lisbon, Portugal;

    Engineering Systems Division and MLT Portugal Program, Massachusetts institute of Technology, Cambridge, MA, USA;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    fuzzy modeling; multi-criteria; feature selection; sensitivity; intensive care unit; septic shock;

    机译：模糊建模多准则特征选择;灵敏度;重症监护室;败血性休克;

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