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Creating a medical English-Swedish dictionary using interactive word alignment
Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.ORCID iD: 0000-0001-6468-2432
Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, NLPLAB - Natural Language Processing Laboratory.
Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, NLPLAB - Natural Language Processing Laboratory.
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2006 (English)In: BMC Medical Informatics and Decision Making, ISSN 1472-6947, Vol. 6, no 35Article in journal (Refereed) Published
Abstract [en]

Background: This paper reports on a parallel collection of rubrics from the medical terminology systems ICD-10, ICF, MeSH, NCSP and KSH97-P and its use for semi-automatic creation of an English-Swedish dictionary of medical terminology. The methods presented are relevant for many other West European language pairs than English-Swedish. Methods: The medical terminology systems were collected in electronic format in both English and Swedish and the rubrics were extracted in parallel language pairs. Initially, interactive word alignment was used to create training data from a sample. Then the training data were utilised in automatic word alignment in order to generate candidate term pairs. The last step was manual verification of the term pair candidates. Results: A dictionary of 31,000 verified entries has been created in less than three man weeks, thus with considerably less time and effort needed compared to a manual approach, and without compromising quality. As a side effect of our work we found 40 different translation problems in the terminology systems and these results indicate the power of the method for finding inconsistencies in terminology translations. We also report on some factors that may contribute to making the process of dictionary creation with similar tools even more expedient. Finally, the contribution is discussed in relation to other ongoing efforts in constructing medical lexicons for non-English languages. Conclusion: In three man weeks we were able to produce a medical English-Swedish dictionary consisting of 31,000 entries and also found hidden translation errors in the utilized medical terminology systems. © 2006 Nyström et al, licensee BioMed Central Ltd.

Place, publisher, year, edition, pages
2006. Vol. 6, no 35
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:liu:diva-35769DOI: 10.1186/1472-6947-6-35Local ID: 28502OAI: oai:DiVA.org:liu-35769DiVA: diva2:256617
Note
Original Publication: Mikael Nyström, Magnus Merkel, Lars Ahrenberg, Pierre Zweigenbaum, Håkan Petersson and Hans Åhlfeldt, Creating a medical English-Swedish dictionary using interactive word alignment, 2006, BMC Medical Informatics and Decision Making, (6), 35. http://dx.doi.org/10.1186/1472-6947-6-35 Licensee: BioMed Central http://www.biomedcentral.com/ Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2015-09-22
In thesis
1. Enrichment of Terminology Systems for Use and Reuse in Medical Information Systems
Open this publication in new window or tab >>Enrichment of Terminology Systems for Use and Reuse in Medical Information Systems
2010 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Electronic health record systems (EHR) are used to store relevant heath facts about patients. The main use of the EHR is in the care of the patient, but an additional use is to reuse the EHR information to locate and evaluate clinical evidence for treatments. To efficiently use the EHR information it is essential to use appropriate methods for information compilations. This thesis deals with use of information in medical terminology systems and ontologies to be able to better use and reuse EHR information and other medical information.

The first objective of the thesis is to examine if word alignment on bilingual English-Swedish rubrics from five medical terminology systems can be used to build a bilingual dictionary. A study found that it was possible to generate a dictionary with 42 000 entries containing a high proportion of medical entries using word alignment. The method worked best using sets of rubrics with many unique words that are consistently translated. The dictionary can be used as a general medical dictionary, for use in semi-automatic translation methods, for use in cross-language information retrieval systems, and for enrichment of other terminology systems.

The second objective of the thesis is to explore how connections from existing terminology systems and information models to SNOMED CT and the structure in SNOMED CT can be used to reuse information. A study examined whether the primary health care diagnose terminology system KSH97-P can obtain a richer structure using category and chapter mappings from KSH97-P to SNOMED CT and the structure in SNOMED CT. The study showed that KSH97-P can be enriched with a poly-hierarchical chapter division and additional attributes. The richer structure was used to compile statistics in new manners that showed new views of the primary care diagnoses. A literature study evaluated which kinds of information compilations those are necessary to create graphical patient overviews based on information from EHRs. It was found that a third of the patient overviews can have their information needs satisfied using compilations based on SNOMED CT encodings of the information entities in the EHR and the structure in SNOMED CT. The other overviews also need access to individual values in the EHR. This can be achieved by using well-defined information models in the EHR.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2010. 79 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1335
National Category
Computer and Information Science
Identifiers
urn:nbn:se:liu:diva-58621 (URN)978-91-7393-328-5 (ISBN)
Public defence
2010-09-10, Eken, Campus US, Linköpings universitet, Linköping, 09:00 (English)
Opponent
Supervisors
Available from: 2010-08-30 Created: 2010-08-18 Last updated: 2015-09-22Bibliographically approved

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