Similarity detection between virtual patients and medical curriculum using R

Publikace nespadá pod Filozofickou fakultu, ale pod Lékařskou fakultu. Oficiální stránka publikace je na webu muni.cz.

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

Druh Článek ve sborníku
Konference Studies in Health Technology and Informatics 255
Fakulta / Pracoviště MU

Lékařská fakulta

Citace
www http://ebooks.iospress.nl/volumearticle/50507
Doi http://dx.doi.org/10.3233/978-1-61499-921-8-222
Klíčová slova OPTIMED; R programming language; akutne.cz; medical curriculum; text similarity; virtual patient
Popis 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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