使用遗传算法优化模糊临床决策支持规则。
Optimizing fuzzy clinical decision support rules using genetic algorithms.
作者信息
Krajnak Michael, Xue Joel
机构信息
GE Healthcare Information Technology, Milwaukee, WI 53226. USA.
出版信息
Conf Proc IEEE Eng Med Biol Soc. 2006;2006:5173-6. doi: 10.1109/IEMBS.2006.260366.
In this paper, we present a technique for optimizing a fuzzy system using a genetic algorithm that works for patient status monitoring in the operating room. The genetic algorithm adjusts rule weights, outputs, and input membership functions to maximize the area under a receiver operator curve (ROC) for final classification. Compared to pre-optimization, the optimized fuzzy inference system increased ROC area from 0.68 to 0.77, which can be translated to an increase in specificity from 74% to 82%, at a fixed sensitivity of 58%
在本文中，我们提出了一种使用遗传算法优化模糊系统的技术，该技术用于手术室中的患者状态监测。遗传算法调整规则权重、输出和输入隶属函数，以最大化最终分类的接收者操作特征曲线（ROC）下的面积。与优化前相比，优化后的模糊推理系统将ROC面积从0.68提高到0.77，在固定灵敏度为58%的情况下，这可以转化为特异性从74%提高到82%。
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