DocumentCode
677853
Title
Challenges in Clinical Named Entity Recognition for Decision Support
Author
Dehghan, Afshin ; Keane, John A. ; Nenadic, Goran
Author_Institution
Sch. of Comput. Sci., Univ. of Manchester, Manchester, UK
fYear
2013
fDate
13-16 Oct. 2013
Firstpage
947
Lastpage
951
Abstract
In addition to structured data, electronic health records contain unstructured clinical notes and narratives. The identification and classification of mentions of relevant clinical concepts is a crucial preprocessing step in designing and developing clinical decision support systems. While this task has gained significant attention in recent years, there are still a number of issues that need further investigation. This paper explores a variety of common challenges faced by clinical named entity recognition and classification methods as well as current approaches to handling them.
Keywords
data structures; decision support systems; electronic health records; pattern classification; classification methods; clinical decision support systems; clinical named entity recognition; electronic health records; structured data; unstructured clinical narratives; unstructured clinical notes; Availability; Data mining; Diseases; Drugs; Medical diagnostic imaging; Terminology; Unified modeling language; Clinical concept extraction; Clinical named entity recognition and classification; Information extraction; Text mining;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on
Conference_Location
Manchester
Type
conf
DOI
10.1109/SMC.2013.166
Filename
6721919
Link To Document