Suppr超能文献

基于计算机的病历中会诊记录的自动分类

Automated classification of encounter notes in a computer based medical record.

作者信息

Aronow D B, Soderland S, Ponte J M, Feng F, Croft W B, Lehnert W G

机构信息

Center for Intelligent Information Retrieval, Lederle Graduate Research Center, University of Massachusetts, Amherst MA 01003 USA.

出版信息

Medinfo. 1995;8 Pt 1:8-12.

PMID:8591332
Abstract

Harvard Community Health Plan is exploring emerging information technologies for means to use the text portion of its 25 year old computerized medical record system. The Center for Intelligent Information Retrieval is developing systems to answer the question: to what extent can automated information systems replace manual chart review of encounter notes? INQUERY, a probabilistic inference net information retrieval system, and FIGLEAF, an inductive decision tree text classifier are applied to the problem of classifying electronic encounter notes to identify acute exacerbations in pediatric asthmatics. Both systems achieve average precisions of greater than 80%, with a new enhancement to INQUERY's relevance feedback, the top performer. Refinement of the systems and plans for their integration are discussed.

摘要

哈佛社区健康计划正在探索新兴信息技术,以利用其已有25年历史的计算机化医疗记录系统中的文本部分。智能信息检索中心正在开发系统,以回答以下问题:自动化信息系统在多大程度上可以取代对会诊记录的人工图表审查?INQUERY(一种概率推理网络信息检索系统)和FIGLEAF(一种归纳决策树文本分类器)被应用于对电子会诊记录进行分类的问题,以识别小儿哮喘患者的急性加重情况。两个系统的平均精度均超过80%,其中INQUERY通过对其相关反馈的新增强成为表现最佳者。文中讨论了系统的优化及其整合计划。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验