Medical Knowledge Resources for Text-Mining of Health Records in Czech, Polish, and Slovak

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F22%3A00127483" target="_blank" >RIV/00216224:14330/22:00127483 - isvavai.cz</a>

Výsledek na webu

<a href="https://nlp.fi.muni.cz/raslan/2022/paper14.pdf" target="_blank" >https://nlp.fi.muni.cz/raslan/2022/paper14.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Medical Knowledge Resources for Text-Mining of Health Records in Czech, Polish, and Slovak

Popis výsledku v původním jazyce

Knowledge extraction from medical text in small languages like Czech, Polish or Slovak is challenging due to the insufficiency of languagespecific medical resources (pretrained models, ontologies, dictionaries). This paper is a survey of noteworthy options for researchers targeting these languages, divided into two sections. First, since the UMLS Metathesaurus for English is by far the most extensive and detailed medical knowledge resource in Western medicine, appreciable results can be achieved by machine-translating the mined text to English – therefore, the relevant English components of UMLS are introduced. Second come the languagespecific resources for each language, detailing the publishing institutions, current website locations, contents, and file formats. The contribution of this paper is in collecting and pre-screening widely disparate sources needed for successful medical knowledge extraction in Central European Slavic languages.

Název v anglickém jazyce

Medical Knowledge Resources for Text-Mining of Health Records in Czech, Polish, and Slovak

Popis výsledku anglicky

Knowledge extraction from medical text in small languages like Czech, Polish or Slovak is challenging due to the insufficiency of languagespecific medical resources (pretrained models, ontologies, dictionaries). This paper is a survey of noteworthy options for researchers targeting these languages, divided into two sections. First, since the UMLS Metathesaurus for English is by far the most extensive and detailed medical knowledge resource in Western medicine, appreciable results can be achieved by machine-translating the mined text to English – therefore, the relevant English components of UMLS are introduced. Second come the languagespecific resources for each language, detailing the publishing institutions, current website locations, contents, and file formats. The contribution of this paper is in collecting and pre-screening widely disparate sources needed for successful medical knowledge extraction in Central European Slavic languages.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10200 - Computer and information sciences

Projekt

<a href="/cs/project/EF19_073%2F0016943" target="_blank" >EF19_073/0016943: Interní grantová agentura Masarykovy univerzity</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the Sixteenth Workshop on Recent Advances in Slavonic Natural Languages Processing, RASLAN 2022

ISBN

9788026317524

ISSN

2336-4289

e-ISSN

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Počet stran výsledku

9

Strana od-do

161-169

Název nakladatele

Tribun EU

Místo vydání

Brno

Místo konání akce

Brno

Datum konání akce

1. 1. 2022

Typ akce podle státní příslušnosti

CST - Celostátní akce

Kód UT WoS článku

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