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Detection of medical text semantic similarity based on convolutional neural network

机译:基于卷积神经网络的医学文本语义相似度检测

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摘要

BackgroundImaging examinations, such as ultrasonography, magnetic resonance imaging and computed tomography scans, play key roles in healthcare settings. To assess and improve the quality of imaging diagnosis, we need to manually find and compare the pre-existing reports of imaging and pathology examinations which contain overlapping exam body sites from electrical medical records (EMRs). The process of retrieving those reports is time-consuming. In this paper, we propose a convolutional neural network (CNN) based method which can better utilize semantic information contained in report texts to accelerate the retrieving process.
机译:背景技术超声检查,磁共振成像和计算机断层扫描等成像检查在医疗机构中发挥着关键作用。为了评估和提高影像诊断的质量,我们需要手动查找和比较影像和病理检查的现有报告,其中包含来自电子病历(EMR)的重叠检查身体部位。检索这些报告的过程非常耗时。在本文中,我们提出了一种基于卷积神经网络(CNN)的方法,该方法可以更好地利用报告文本中包含的语义信息来加快检索过程。

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