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28 March 2024 |
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Article overview
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A Concept Annotation System for Clinical Records | Ning Kang
; Rogier Barendse
; Zubair Afzal
; Bharat Singh
; Martijn J. Schuemie
; Erik M. van Mulligen
; Jan A. Kors
; | Date: |
8 Dec 2010 | Abstract: | Unstructured information comprises a valuable source of data in clinical
records. For text mining in clinical records, concept extraction is the first
step in finding assertions and relationships. This study presents a system
developed for the annotation of medical concepts, including medical problems,
tests, and treatments, mentioned in clinical records. The system combines six
publicly available named entity recognition system into one framework, and uses
a simple voting scheme that allows to tune precision and recall of the system
to specific needs. The system provides both a web service interface and a UIMA
interface which can be easily used by other systems. The system was tested in
the fourth i2b2 challenge and achieved an F-score of 82.1% for the concept
exact match task, a score which is among the top-ranking systems. To our
knowledge, this is the first publicly available clinical record concept
annotation system. | Source: | arXiv, 1012.1663 | Services: | Forum | Review | PDF | Favorites |
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