D 2018

Similarity detection between virtual patients and medical curriculum using R

KOMENDA, Martin, Jakub ŠČAVNICKÝ, Petra RŮŽIČKOVÁ, Matěj KAROLYI, Petr ŠTOURAČ et. al.

Basic information

Original name

Similarity detection between virtual patients and medical curriculum using R

Authors

KOMENDA, Martin (203 Czech Republic, belonging to the institution), Jakub ŠČAVNICKÝ (703 Slovakia, belonging to the institution), Petra RŮŽIČKOVÁ (203 Czech Republic, belonging to the institution), Matěj KAROLYI (203 Czech Republic, belonging to the institution), Petr ŠTOURAČ (203 Czech Republic, belonging to the institution) and Daniel SCHWARZ (203 Czech Republic, belonging to the institution)

Edition

Amsterdam, Studies in Health Technology and Informatics 255, p. 222-226, 5 pp. 2018

Publisher

IOS Press

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

20601 Medical engineering

Country of publisher

Netherlands

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

References:

RIV identification code

RIV/00216224:14110/18:00104412

Organization unit

Faculty of Medicine

ISBN

978-1-61499-920-1

ISSN

DOI

UT WoS

000455957400043

Keywords in English

OPTIMED; R programming language; akutne.cz; medical curriculum; text similarity; virtual patient

Tags

Změněno: 2/5/2019 14:21, Soňa Böhmová

Abstract

V originále

This paper presents the domain of information sciences, applied informatics and biomedical engineering, proposing to develop methods for an automated detection of similarities between two particular virtual learning environments - virtual patients at Akutne.cz and the OPTIMED curriculum management system - in order to provide support to clinically oriented stages of medical and healthcare studies. For this purpose, the authors used large amounts of text-based data collected by the system for mapping medical curricula and through the system for virtual patient authoring and delivery. The proposed text-mining algorithm for an automated detection of links between content entities of these systems has been successfully implemented by the means of a web-based toolbox.

Links

CZ.02.2.67/0.0/0.0/16_016/0002416, interní kód MU
Name: Strategické investice Masarykovy univerzity do vzdělávání SIMU+
Investor: Ministry of Education, Youth and Sports of the CR, Priority axis 2: Development of universities and human resources for research and development
CZ.02.2.69/0.0/0.0/16_015/0002418, interní kód MU
Name: Masarykova univerzita 4.0 (Acronym: MUNI 4.0)
Investor: Ministry of Education, Youth and Sports of the CR, Priority axis 2: Development of universities and human resources for research and development
MUNI/A/1339/2016, interní kód MU
Name: MERGER: detekce vazeb mezi informačními systémy pro mapování kurikula a pro virtuální pacienty (Acronym: MERGER)
Investor: Masaryk University, Category A