D 2016

Automatic Keyword Extraction from Medical and Healthcare Curriculum

KOMENDA, Martin, Matěj KAROLYI, Andrea POKORNÁ, Martin VÍTA, Vincent KRÍŽ et. al.

Basic information

Original name

Automatic Keyword Extraction from Medical and Healthcare Curriculum

Authors

KOMENDA, Martin (203 Czech Republic, guarantor, belonging to the institution), Matěj KAROLYI (203 Czech Republic, belonging to the institution), Andrea POKORNÁ (203 Czech Republic, belonging to the institution), Martin VÍTA (203 Czech Republic, belonging to the institution) and Vincent KRÍŽ (203 Czech Republic)

Edition

Warzaw; Los Alamitos, Annals of Computer Science and Information Systems, Volume 8 : Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, p. 287-290, 4 pp. 2016

Publisher

Polskie Towarzystwo Informatyczne; Institute of Electrical and Electronics Engineers

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Poland

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

References:

URL

RIV identification code

RIV/00216224:14110/16:00090196

Organization unit

Faculty of Medicine

ISBN

978-83-60810-90-3

ISSN

DOI

http://dx.doi.org/10.15439/2016F156

UT WoS

000392436600045

Keywords in English

automatic keyword extraction; medical and healthcare curriculum; CRIPS-DM

Tags

EL OK, firank_B, OPTIMED, podil

Tags

International impact, Reviewed
Změněno: 27/4/2020 14:13, Mgr. Tereza Miškechová

Abstract

V originále

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.

Links

2014-1-CZ01-KA203-002002, interní kód MU
Name: Clinical ReasOning skills Enhancements with the use of SimUlations and algorithmS (Acronym: CROESUS)
Investor: European Union, Strategic Partnerships in the field of education, training and youth
2015-1-CZ01-KA203-013935, interní kód MU
Name: Medical Curriculum Innovations (Acronym: MEDCIN)
Investor: European Union, Strategic Partnerships in the field of education, training and youth
Displayed: 1/11/2024 04:48