Detailed Information on Publication Record
2017
A Pilot Medical Curriculum Analysis and Visualization According to Medbiquitous Standards
KOMENDA, Martin, Matěj KAROLYI, Christos VAITSIS, Dimitris SPACHOS, Luke WOODHAM et. al.Basic information
Original name
A Pilot Medical Curriculum Analysis and Visualization According to Medbiquitous Standards
Authors
KOMENDA, Martin (203 Czech Republic, guarantor, belonging to the institution), Matěj KAROLYI (203 Czech Republic, belonging to the institution), Christos VAITSIS (752 Sweden), Dimitris SPACHOS (300 Greece) and Luke WOODHAM (826 United Kingdom of Great Britain and Northern Ireland)
Edition
Los Alamitos, 2017 IEEE 30th International Symposium on Computer-Based Medical Systems, p. 144-149, 6 pp. 2017
Publisher
IEEE Computer Society
Other information
Language
English
Type of outcome
Stať ve sborníku
Field of Study
10201 Computer sciences, information science, bioinformatics
Country of publisher
Canada
Confidentiality degree
není předmětem státního či obchodního tajemství
Publication form
electronic version available online
References:
RIV identification code
RIV/00216224:14110/17:00098489
Organization unit
Faculty of Medicine
ISBN
978-1-5386-1710-6
ISSN
UT WoS
000424864800029
Keywords in English
Medical and healthcare education; standardization; data analysis; data visualization
Tags
Změněno: 13/3/2018 13:13, Soňa Böhmová
Abstract
V originále
Curriculum design and implementation in higher medical education can be a great challenge. Although there are well-defined standards, such as the Curriculum Inventory and Competency Framework by MedBiquitous Consortium, existing systems are incapable of a visual representation of the various components, attributes, and relations. In this paper, we present the MEDCIN platform, a pilot tool which uses a standard-compliant curriculum data model to offer comprehensive and thorough analysis of a given curriculum. In addition, the ongoing research in challenging areas, such as the curriculum content comparison, can reveal valuable knowledge from existing data and transform the future of medical education.