title: A normalized lexical lookup approach to identifying UMLS concepts in free text.
abstract: The National Library of Medicine has developed a tool to identify medical concepts from the Unified Medical Language System in free text. This tool - MetaMap (and its java version MMTx) has been used extensively for biomedical text mining applications. We have developed a module for MetaMap which has a high performance in terms of processing speed. We evaluated our module independently against MetaMap for the task of identifying UMLS concepts in free text clinical radiology reports. A set of 1000 sentences from neuro-radiology reports were collected and processed using our technique and the MMTx Program. An evaluation showed that our technique was able to identify 91% of the concepts found by MMTx in 14% of the time taken by MMTx. An error analysis showed that the missing concepts were largely those which were not direct lexical matches but inferential matches of multiple concepts. Our method also identified multi-phrase concepts which MMTx failed to identify. We suggest that this module be implemented as an option in MMTx for real-time text mining applications where single concepts found in the UMLS need to be identified.
authors.affiliation: Medical Imaging Informatics Group, University of California, Los Angeles, United States. vbashyam@ucla.edu
authors.forename: Vijayaraghavan
authors.initials: V
authors.lastname: Bashyam
authors.forename: Guy
authors.initials: G
authors.lastname: Divita
authors.forename: David B
authors.initials: DB
authors.lastname: Bennett
authors.forename: Allen C
authors.initials: AC
authors.lastname: Browne
authors.forename: Ricky K
authors.initials: RK
authors.lastname: Taira
mesh_terms: D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D016347:Medical Records Systems, Computerized; D009323:Natural Language Processing; D009462:Neurology; D011872:Radiology Department, Hospital; D011873:Radiology Information Systems; D017432:Unified Medical Language System