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引用次数: 0

摘要

诊断心脏病对医生来说是一个具有挑战性的过程。专家人数不足、诊断晚、误诊是这一过程中的难点。为了克服这些困难,今天使用了基于人工智能的系统。适当的系统选择和获得足够的数据集是研究人员面临的挑战。本研究提出了一种用于心脏病检测的高性能CAD体系结构。所提出的架构比文献中使用UCI数据集进行的研究显示出更高的性能。
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A System Architecture Based on The RNN Classifier for Heart Disease Detection
Diagnosing heart disease is a challenging process for physicians. Insufficient number of experts, late diagnosis and misdiagnosis are the difficulties in this process. To overcome these difficulties, systems based on artificial intelligence are used today. Appropriate system selection and obtaining sufficient data sets are a challenge for researchers. In this study, a high-performance CAD architecture was proposed for the detection of heart disease. The proposed architecture has shown a higher performance than the studies carried out using the UCI dataset in the literature.
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