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Similarity Detection Between Virtual Patients and Medical Curriculum Using R

M. Komenda, J. Ščavnický, P. Růžičková, M. Karolyi, P. Štourač, D. Schwarz,

. 2018 ; 255 (-) : 222-226. [pub] -

Language English Country Netherlands

Document type Journal Article

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