Automatic Keyword Extraction from Medical and Healthcare Curriculum

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F16%3A10335481" target="_blank" >RIV/00216208:11320/16:10335481 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216224:14110/16:00090196

Výsledek na webu

<a href="http://dx.doi.org/10.15439/2016F156" target="_blank" >http://dx.doi.org/10.15439/2016F156</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.15439/2016F156" target="_blank" >10.15439/2016F156</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Automatic Keyword Extraction from Medical and Healthcare Curriculum

Popis výsledku v původním jazyce

Medical and healthcare study programmes are quite complicated in terms of branched structure and heterogeneous content. In logical sequence a lot of requirements and demands placed on students appear there. This paper focuses on an innovative way how to discover and understand complex curricula using modern information and communication technologies. We introduce an algorithm for curriculum metadata automatic processing -- automatic keyword extraction based on unsupervised approaches, and we demonstrate a real application during a process of innovation and optimization of medical education. The outputs of our pilot analysis represent systematic description of medical curriculum by three different approaches (centrality measures) used for relevant keywords extraction. Further evaluation by senior curriculum designers and guarantors is required to obtain an objective benchmark.

Název v anglickém jazyce

Automatic Keyword Extraction from Medical and Healthcare Curriculum

Popis výsledku anglicky

Medical and healthcare study programmes are quite complicated in terms of branched structure and heterogeneous content. In logical sequence a lot of requirements and demands placed on students appear there. This paper focuses on an innovative way how to discover and understand complex curricula using modern information and communication technologies. We introduce an algorithm for curriculum metadata automatic processing -- automatic keyword extraction based on unsupervised approaches, and we demonstrate a real application during a process of innovation and optimization of medical education. The outputs of our pilot analysis represent systematic description of medical curriculum by three different approaches (centrality measures) used for relevant keywords extraction. Further evaluation by senior curriculum designers and guarantors is required to obtain an objective benchmark.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

—

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the 2016 Federated Conference on Computer Science and Information Systems

ISBN

978-83-60810-90-3

ISSN

2300-5963

e-ISSN

—

Počet stran výsledku

4

Strana od-do

287-290

Název nakladatele

Institute of Electrical and Electronics Engineers

Místo vydání

New York City, NY, USA

Místo konání akce

Gdańsk, Poland

Datum konání akce

11. 9. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—