Publication details

Automatic Keyword Extraction from Medical and Healthcare Curriculum

Investor logo
Investor logo
Authors

KOMENDA Martin KAROLYI Matěj POKORNÁ Andrea VÍTA Martin KRÍŽ Vincent

Year of publication 2016
Type Article in Proceedings
Conference Annals of Computer Science and Information Systems, Volume 8 : Proceedings of the 2016 Federated Conference on Computer Science and Information Systems
MU Faculty or unit

Faculty of Medicine

Citation
web https://fedcsis.org/proceedings/2016/drp/156.html
Doi http://dx.doi.org/10.15439/2016F156
Field Informatics
Keywords automatic keyword extraction; medical and healthcare curriculum; CRIPS-DM
Description Medical and healthcare study programmes are quite complicated in terms of branched structure and heterogeneous content. In logical sequence a lot of requirements and demands placed on students appear there. This paper focuses on an innovative way how to discover and understand complex curricula using modern information and communication technologies. We introduce an algorithm for curriculum metadata automatic processing -- automatic keyword extraction based on unsupervised approaches, and we demonstrate a real application during a process of innovation and optimization of medical education. The outputs of our pilot analysis represent systematic description of medical curriculum by three different approaches (centrality measures) used for relevant keywords extraction. Further evaluation by senior curriculum designers and guarantors is required to obtain an objective benchmark.
Related projects:

You are running an old browser version. We recommend updating your browser to its latest version.

More info