Publication details

Similarity detection between virtual patients and medical curriculum using R

Authors

KOMENDA Martin ŠČAVNICKÝ Jakub RŮŽIČKOVÁ Petra KAROLYI Matěj ŠTOURAČ Petr SCHWARZ Daniel

Year of publication 2018
Type Article in Proceedings
Conference Studies in Health Technology and Informatics 255
MU Faculty or unit

Faculty of Medicine

Citation
Web http://ebooks.iospress.nl/volumearticle/50507
Doi http://dx.doi.org/10.3233/978-1-61499-921-8-222
Keywords OPTIMED; R programming language; akutne.cz; medical curriculum; text similarity; virtual patient
Description 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.
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