...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of biomedical informatics. >Extracting information on pneumonia in infants using natural language processing of radiology reports.
【24h】

Extracting information on pneumonia in infants using natural language processing of radiology reports.

机译：使用放射学报告的自然语言处理来提取婴儿肺炎的信息。

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Natural language processing (NLP) is critical for improvement of the healthcare process because it can encode clinical data in patient documents. Many clinical applications such as decision support require coded data to function appropriately. However, in order to be applicable for healthcare, performance must be adequate. A valuable automated application is the detection of infectious diseases, such as surveillance of pneumonia in newborns (e.g., neonates) because the disease produces significant rates of morbidity and mortality, and manual surveillance is challenging. Studies have demonstrated that automated surveillance using NLP is a useful adjunct to manual surveillance and an effective tool for infection control practitioners. This paper presents a study evaluating the feasibility of an NLP-based monitoring system to screen for healthcare-associated pneumonia in neonates. We estimated sensitivity, specificity, and positive predictive value by comparing results with clinicians' judgments. Sensitivity was 71% and specificity was 99%. Our results demonstrated that the automated method was feasible.
机译：自然语言处理（NLP）对于改善医疗保健流程至关重要，因为它可以对患者文档中的临床数据进行编码。许多临床应用（例如决策支持）需要编码数据才能正常运行。但是，为了适用于医疗保健，性能必须足够。一种有价值的自动化应用是检测传染性疾病，例如监测新生儿（例如新生儿）的肺炎，因为该疾病会导致很高的发病率和死亡率，并且人工监测具有挑战性。研究表明，使用NLP进行自动监视是手动监视的有用辅助手段，并且是感染控制从业人员的有效工具。本文提出了一项评估基于NLP的监测系统筛查新生儿保健相关肺炎的可行性的研究。通过将结果与临床医生的判断进行比较，我们估计了敏感性，特异性和阳性预测价值。敏感性为71％，特异性为99％。我们的结果表明自动化方法是可行的。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号