This HTML5 document contains 47 embedded RDF statements represented using HTML+Microdata notation.

The embedded RDF content will be recognized by any processor of HTML5 Microdata.

Namespace Prefixes

PrefixIRI
n20http://linked.opendata.cz/ontology/domain/vavai/riv/typAkce/
dctermshttp://purl.org/dc/terms/
n15http://localhost/temp/predkladatel/
n13http://purl.org/net/nknouf/ns/bibtex#
n21http://linked.opendata.cz/resource/domain/vavai/projekt/
n9http://linked.opendata.cz/resource/domain/vavai/riv/tvurce/
n11http://linked.opendata.cz/ontology/domain/vavai/
n16https://schema.org/
shttp://schema.org/
n14http://linked.opendata.cz/resource/domain/vavai/vysledek/RIV%2F68407700%3A21230%2F08%3A03141897%21RIV09-AV0-21230___/
skoshttp://www.w3.org/2004/02/skos/core#
n3http://linked.opendata.cz/ontology/domain/vavai/riv/
n2http://linked.opendata.cz/resource/domain/vavai/vysledek/
rdfhttp://www.w3.org/1999/02/22-rdf-syntax-ns#
n4http://linked.opendata.cz/ontology/domain/vavai/riv/klicoveSlovo/
n10http://linked.opendata.cz/ontology/domain/vavai/riv/duvernostUdaju/
xsdhhttp://www.w3.org/2001/XMLSchema#
n17http://linked.opendata.cz/ontology/domain/vavai/riv/jazykVysledku/
n6http://linked.opendata.cz/ontology/domain/vavai/riv/aktivita/
n18http://linked.opendata.cz/ontology/domain/vavai/riv/druhVysledku/
n7http://linked.opendata.cz/ontology/domain/vavai/riv/obor/
n8http://reference.data.gov.uk/id/gregorian-year/

Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F08%3A03141897%21RIV09-AV0-21230___
rdf:type
n11:Vysledek skos:Concept
dcterms:description
Patients health records offer a rich source of information about the diseases, their symptoms and development. However, most of the records currently available are in form of semi structured text files the content of which cannot be accessed by technical means in a straightforward way. In order to apply some automated reasoning techniques, the content of the patient record has to be transformed from the textual form into a new machine-understandable format. Our intention is to use for that purpose OWL formalism. The knowledge base in OWL is created by means of semantic annotation using ontologies. Instances of this knowledge base can be exported to a relational database. Due to specific features of medical language, the current natural language processing techniques do not allow us to perform this annotation automatically. Medical records Annotation Tool (MedAT) provides a framework for semiautomatic semantic annotation of patients records. Patients health records offer a rich source of information about the diseases, their symptoms and development. However, most of the records currently available are in form of semi structured text files the content of which cannot be accessed by technical means in a straightforward way. In order to apply some automated reasoning techniques, the content of the patient record has to be transformed from the textual form into a new machine-understandable format. Our intention is to use for that purpose OWL formalism. The knowledge base in OWL is created by means of semantic annotation using ontologies. Instances of this knowledge base can be exported to a relational database. Due to specific features of medical language, the current natural language processing techniques do not allow us to perform this annotation automatically. Medical records Annotation Tool (MedAT) provides a framework for semiautomatic semantic annotation of patients records. Lékařské záznamy nabízí bohatý zdroj informací o nemocech, jejich symptomech a průběhu. Bohužel většina záznamů je dostupná pouze ve formě textového souboru nebo pouze v papírové podobě, což jsou formáty, které nelze jednoduše počítačově zpracovat. V tomto článku představujeme systém MedAT (Medical Annotation Tool) jako podpůrný nástroj pro převod lékařských záznamů do strukturované formy, která je vytvořena systémem ontologií v OWL formalismu.
dcterms:title
Ontologie pro anotaci a analýzu lékařských záznamů Ontologies in Annotation and Analysis of Medical Records Ontologies in Annotation and Analysis of Medical Records
skos:prefLabel
Ontologies in Annotation and Analysis of Medical Records Ontologies in Annotation and Analysis of Medical Records Ontologie pro anotaci a analýzu lékařských záznamů
skos:notation
RIV/68407700:21230/08:03141897!RIV09-AV0-21230___
n3:aktivita
n6:P
n3:aktivity
P(1ET101210513)
n3:dodaniDat
n8:2009
n3:domaciTvurceVysledku
n9:7943555 n9:9942904 n9:5112605
n3:druhVysledku
n18:D
n3:duvernostUdaju
n10:S
n3:entitaPredkladatele
n14:predkladatel
n3:idSjednocenehoVysledku
384888
n3:idVysledku
RIV/68407700:21230/08:03141897
n3:jazykVysledku
n17:eng
n3:klicovaSlova
annotation; ontology; text mining
n3:klicoveSlovo
n4:annotation n4:ontology n4:text%20mining
n3:kontrolniKodProRIV
[FB5F9A08532E]
n3:mistoKonaniAkce
Athens
n3:mistoVydani
Praha
n3:nazevZdroje
Distributed Human-Machine Systems
n3:obor
n7:JC
n3:pocetDomacichTvurcuVysledku
3
n3:pocetTvurcuVysledku
4
n3:projekt
n21:1ET101210513
n3:rokUplatneniVysledku
n8:2008
n3:tvurceVysledku
Maříková, T. Žáková, Monika Štěpánková, Olga Nováková, Lenka
n3:typAkce
n20:WRD
n3:zahajeniAkce
2008-03-09+01:00
s:numberOfPages
6
n13:hasPublisher
Česká technika - nakladatelství ČVUT
n16:isbn
978-80-01-04027-0
n15:organizacniJednotka
21230