Skip to main navigation Skip to search Skip to main content

Lexical acquisition for clinical text mining using distributional similarity

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

    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
    PublisherSpringer Verlag
    Pages232-246
    Number of pages15
    EditionPART 2
    ISBN (Print)9783642286001
    DOIs
    StatePublished - 2012
    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

    Fingerprint

    Dive into the research topics of 'Lexical acquisition for clinical text mining using distributional similarity'. Together they form a unique fingerprint.

    Cite this