Authors:
Natalia Grabar
1
;
Izak van Zyl
2
;
Retha de la Harpe
2
and
Thierry Hamon
3
Affiliations:
1
Université Lille 1&3, France
;
2
Cape Peninsula University of Technology, South Africa
;
3
LIMSI-CNRS, BP133 and Université Paris 13, France
Keyword(s):
Health Literacy, Readability, Consumer Health Informatics, Natural Language Processing, Xhosa, French.
Related
Ontology
Subjects/Areas/Topics:
Biomedical Engineering
;
Cardiovascular Technologies
;
Cloud Computing
;
Computing and Telecommunications in Cardiology
;
e-Health
;
Health Engineering and Technology Applications
;
Health Information Systems
;
ICT, Ageing and Disability
;
Medical and Nursing Informatics
;
Platforms and Applications
Abstract:
This paper presents cross-lingual experiments in automatic detection of medical words that may be difficult to understand by patients. The study relies on Natural Language Processing (NLP) methods, conducted in three steps, across two languages, French and Xhosa: (1) the French data are processed by NLP methods and tools to reproduce the manual categorization of words as understandable or not; (2) the Xhosa data are clustered with a non-supervised algorithm; (3) an analysis of the Xhosa results and their comparison with the results observed on the French data is performed. Some similarities between the two languages are observed.