Extracting specific medical data using semantic structures

被引：0
|
作者：
Denecke, Kerstin [1 ,2 ]
Bernauer, Jochen [3 ]
机构：
[1] Tech Univ Carolo Wilhelmina Braunschweig, Muhlenpfordtstr 23, D-38106 Braunschweig, Germany
[2] Leibniz Univ Hannover, Res Ctr L3S, D-30167 Hannover, Germany
[3] Univ Appl Sci, D-89075 Ulm, Germany
来源：
ARTIFICIAL INTELLIGENCE IN MEDICINE, PROCEEDINGS | 2007年 / 4594卷
关键词：
information extraction; natural language understanding; natural language processing;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we discuss the architecture, functionality and performance of a medical information extraction system. The system is based on an approach to automatic generation of semantic structures for free-text. Using a multiaxial nomenclature (Wingert Nomenclature) and existing language-engineering technologies, a conceptual graph-like representation is produced for each sentence of a text. These semantic structures are then exploited to extract information. The components that might be adopted for processing texts in another language than German are identified. Results of first evaluations of the system's performance in an information extraction (IE) subtask in the medical domain are presented: The filling of selected template slots obtained values of 81-95% precision and 83-97% recall.
引用
收藏
页码：257 / 264
页数：8
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