Corpus of Authentic Clinical Diagnoses: Sketch Engine as a Tool for Innovative Approach to Teaching Latin Medical Terminology

This publication doesn't include Faculty of Arts. It includes Language Centre. Official publication website can be found on muni.cz.

Authors

POŘÍZKOVÁ Kateřina BLAHUŠ Marek

Type Appeared in Conference without Proceedings
MU Faculty or unit

Language Centre

Citation
Description Clinical terms represent one of the key issues in the area of teaching Latin medical terminology. Since no internationally valid nomenclature of the clinical terms exists, teachers of medical Latin have to rely mainly on primary and secondary literature of the preclinical and clinical subjects, as well as the biomedical dictionaries and the very limited and difficult access to authentic medical records (due to to the content comprising patients’ and physicians’ sensitive personal data). The Masaryk University Language Centre in Brno has developed innovative approaches to teaching Latin medical terminology. The main emphasis is put on providing students with the knowledge of basic relevant Latin lexico-grammatical features via using authentic materials. In cooperation with several teaching hospitals in Prague and Brno, a unique database of authentic clinical data has been created, containing anonymous diagnoses written by selected (particularly surgical) clinics during the last two or three years. The use of corpus linguistics tools offers many possibilities for medical Latin teachers, one of them being the possibility to work efficiently with this database. It was the Sketch Engine, co-developed by the Natural Language Processing Centre at Masaryk University’ s Faculty of Informatics, which has been chosen as the most suitable corpus linguistics tool for this goal. With the help of this software, we are capable of analyzing and searching the corpus of Latin clinical diagnoses, currently being developed at the Language Centre. The workshop participants will be introduced to various ways of using the corpus for looking up the frequencies of terms, common collocations or occurrences of prepositional cases in clinical diagnoses. They will also learn how to apply these corpus-based linguistic analyses for developing novel teaching and testing materials.
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