Medical free-text to concept mapping as an information retrieval problem
Mirhosseini, Shahin, Zuccon, Guido, Koopman, Bevan, Nguyen, Anthony, & Lawley, Michael (2014) Medical free-text to concept mapping as an information retrieval problem. In Culpepper, J. Shane, Park, Laurence, & Zuccon, Guido (Eds.) Proceedings of the 2014 Australasian Document Computing Symposium, Association for Computing Machinery, Melbourne, VIC, pp. 93-96.
Concept mapping involves determining relevant concepts from a free-text input, where concepts are defined in an external reference ontology. This is an important process that underpins many applications for clinical information reporting, derivation of phenotypic descriptions, and a number of state-of-the-art medical information retrieval methods. Concept mapping can be cast into an information retrieval (IR) problem: free-text mentions are treated as queries and concepts from a reference ontology as the documents to be indexed and retrieved. This paper presents an empirical investigation applying general-purpose IR techniques for concept mapping in the medical domain. A dataset used for evaluating medical information extraction is adapted to measure the effectiveness of the considered IR approaches. Standard IR approaches used here are contrasted with the effectiveness of two established benchmark methods specifically developed for medical concept mapping. The empirical findings show that the IR approaches are comparable with one benchmark method but well below the best benchmark.
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|Item Type:||Conference Paper|
|Keywords:||Concept Mapping, Information Extraction|
|Divisions:||Current > Schools > School of Information Systems
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Copyright Owner:||Copyright 2014 Association for Computing Machinery|
|Deposited On:||20 Oct 2015 04:34|
|Last Modified:||20 Oct 2015 04:34|
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