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
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;
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on
Conference_Location :
Manchester
DOI :
10.1109/SMC.2013.166