Lexical acquisition for clinical text mining using distributional similarity

John Carroll, Rob Koeling, Shivani Puri

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations

Abstract

We describe experiments into the use of distributional similarity for acquiring lexical information from clinical free text, in particular notes typed by primary care physicians (general practitioners). We also present a novel approach to lexical acquisition from 'sensitive' text, which does not require the text to be manually anonymised - a very expensive process - and therefore allows much larger datasets to be used than would normally be possible.

Original languageEnglish
Title of host publicationComputational Linguistics and Intelligent Text Processing - 13th International Conference, CICLing 2012, Proceedings
Pages232-246
Number of pages15
EditionPART 2
DOIs
StatePublished - 2012
Externally publishedYes
Event13th Annual Conference on Intelligent Text Processing and Computational Linguistics, CICLing 2012 - New Delhi, India
Duration: Mar 11 2012Mar 17 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume7182 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th Annual Conference on Intelligent Text Processing and Computational Linguistics, CICLing 2012
Country/TerritoryIndia
CityNew Delhi
Period03/11/1203/17/12

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