DocumentCode :
2541274
Title :
Semantic analysis of free text and its application on automatically assigning ICD-9-CM codes to patient records
Author :
Chen, Ping ; Barrera, Araly ; Rhodes, Chris
Author_Institution :
Dept. of Comput. & Math. Sci., Univ. of Houston-Downtown, Houston, TX, USA
fYear :
2010
fDate :
7-9 July 2010
Firstpage :
68
Lastpage :
74
Abstract :
Free text written in natural languages is lack of definite structures, and semantic analysis of such text is critically important to many Natural Language Processing applications. In this paper, based on dependency parsing, we present a semantic analytic technique to automatically assign clinical ICD-9-CM codes to complex medical patient records written in English. Our semantics analysis method includes dependency parsing of clinical records obtained from testing and training data sets and the calculation of semantic matching scores. Our ultimate goal is to develop an automated disease diagnosis tool through accurate clinical code assignments. We evaluated our technique with a real-world corpus utilized in the 2007 International Natural Language Processing Challenge administered by the Computational Medicine Center at the Cincinnati Children´s Hospital, and obtained promising results.
Keywords :
medical information systems; natural language processing; text analysis; Cincinnati; clinical ICD-9-CM codes assignment; clinical code assignment; clinical record; computational medicine center; data set training; medical patient record; natural language processing; semantic analysis; semantic analytic technique; semantic matching score; Lungs; Medical diagnostic imaging; Medical services; Natural language processing; Semantics; Testing; Training; Automatic Diagnosis; Dependency parsing; Natural Language processing; Semantic analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cognitive Informatics (ICCI), 2010 9th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-8041-8
Type :
conf
DOI :
10.1109/COGINF.2010.5599783
Filename :
5599783
Link To Document :
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