Approaches to text mining for clinical medical records

Clinical medical records contain a wealth of information, largely in free-text form. Means to extract structured information from free-text records is an important research endeavor. In this paper, we describe a MEDical Information Extraction (MedIE) system that extracts and mines a variety of patient information with breast complaints from free-text clinical records. MedIE is a part of medical text mining project being conducted in Drexel University. Three approaches are proposed to solve different IE tasks and very good performance (precision and recall) was achieved. A graph-based approach which uses the parsing result of link-grammar parser was invented for relation extraction; high accuracy was achieved. A simple but efficient ontology-based approach was adopted to extract medical terms of interest. Finally, an NLP-based feature extraction method coupled with an ID3-based decision tree was used to perform text classification. Categories and Subject Descriptors I.2.7 [Natural Lang...

• Type: Conference
• Year: 2006
• Where: SAC
• Authors: Xiaohua Zhou, Hyoil Han, Isaac Chankai, Ann Prestrud, Ari D. Brooks
• Keywords: Applied Computing, Free-text, Information Extraction, Relation Extraction, SAC 2006