Architecture of a Medical Information Extraction System
Identifieur interne : 001395 ( Main/Exploration ); précédent : 001394; suivant : 001396Architecture of a Medical Information Extraction System
Auteurs : Dalila Bekhouche [France, Niger] ; Yann Pollet [France] ; Bruno Grilheres [France, Niger] ; Xavier Denis [France]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2004.
Abstract
Abstract: We present in this article an innovative architecture of information extraction system applied to the medical domain. The content of documents (free texts) can be described or reduced to some relevant information. Our aim is to set a process in order to exploit efficiently the content of the documents. We will explain that the medical information extraction task can be analysed into three steps: Extraction “identify and extract a set of events and entities like date, names, medical terms”, Generation “create from these events and entities the relevant information”, Knowledge acquisition “validate and correct the extraction and generation results”. These analysis require to make various approaches in linguistic, statistic and artificial intelligent cooperate and use together specialised terminology as medical nomenclatures ICD-10 and CCMA and linguistic resources.
Url:
DOI: 10.1007/978-3-540-27779-8_35
Affiliations:
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