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首页> 外文期刊>International Journal of Scientific & Technology Research >An Evolutionary Approach To Cascade Multiple Classifiers: A Case-Study To Analyze Textual Content Of Medical Records And Identify Potential Diagnosis
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An Evolutionary Approach To Cascade Multiple Classifiers: A Case-Study To Analyze Textual Content Of Medical Records And Identify Potential Diagnosis

机译:级联多个分类器的进化方法:个案研究以分析病历的文本内容并确定潜在的诊断

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Abstract: This paper describes an experiment where classifiers are used to identify potential diagnoses on examining textual content of medical records. Three classifiers are applied separately (k-nearest neighborhood, multilayer perceptron and support vector machines) and also combined in two different approaches (parallel and cascading); results show that even accuracy point to a best alternative, ROC analysis show that choosing an approach depends on an acceptable error level.
机译:摘要:本文描述了一个实验,其中使用分类器来识别检查病历文本内容的潜在诊断。分别应用三个分类器(k近邻,多层感知器和支持向量机),并以两种不同的方法(并行和级联)组合使用;结果表明,即使准确性也指向最佳替代方案,ROC分析表明,选择一种方法取决于可接受的错误级别。

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