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Automatic identification of pneumonia related concepts on chest x-ray reports.

机译:在胸部X光报告上自动识别与肺炎有关的概念。

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摘要

A medical language processing system called SymText, two other automated methods, and a lay person were compared against an internal medicine resident for their ability to identify pneumonia related concepts on chest x-ray reports. Sensitivity (recall), specificity, and positive predictive value (precision) are reported with respect to an independent panel of physicians. Overall the performance of SymText was similar to the physician and superior to the other methods. The automatic encoding of pneumonia concepts will support clinical research, decision making, computerized clinical protocols, and quality assurance in a radiology department.
机译:将一种名为SymText的医学语言处理系统,另外两种自动化方法和一个外行与内科住院医师进行比较,以了解他们在X光胸片报告中识别与肺炎相关的概念的能力。关于独立医师小组,报告了敏感性(召回率),特异性和阳性预测值(准确性)。总体而言,SymText的性能类似于医师,并且优于其他方法。肺炎概念的自动编码将支持放射科的临床研究,决策,计算机化的临床方案和质量保证。

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