Hostname: page-component-7d684dbfc8-csfzr Total loading time: 0 Render date: 2023-09-23T14:58:28.866Z Has data issue: false Feature Flags: { "corePageComponentGetUserInfoFromSharedSession": true, "coreDisableEcommerce": false, "coreDisableSocialShare": false, "coreDisableEcommerceForArticlePurchase": false, "coreDisableEcommerceForBookPurchase": false, "coreDisableEcommerceForElementPurchase": false, "coreUseNewShare": true, "useRatesEcommerce": true } hasContentIssue false

Swedification patterns of Latin and Greek affixes in clinical text

Published online by Cambridge University Press:  07 January 2016

Gintarė Grigonytė
Department of Linguistics, Stockholm University, 106 91 Stockholm, Sweden.
Maria Kvist
Department of Computer and Systems Sciences, Stockholm University, Postbox 7003, 164 07 Kista, Sweden.
Mats Wirén
Department of Linguistics, Stockholm University, 106 91 Stockholm, Sweden.
Sumithra Velupillai
Department of Computer and Systems Sciences, Stockholm University, Postbox 7003, 164 07 Kista, Sweden.
Aron Henriksson
Department of Computer and Systems Sciences, Stockholm University, Postbox 7003, 164 07 Kista, Sweden.
Get access


Swedish medical language is rich with Latin and Greek terminology which has undergone a Swedification since the 1980s. However, many original expressions are still used by clinical professionals. The goal of this study is to obtain precise quantitative measures of how the foreign terminology is manifested in Swedish clinical text. To this end, we explore the use of Latin and Greek affixes in Swedish medical texts in three genres: clinical text, scientific medical text and online medical information for laypersons. More specifically, we use frequency lists derived from tokenised Swedish medical corpora in the three domains, and extract word pairs belonging to types that display both the original and Swedified spellings. We describe six distinct patterns explaining the variation in the usage of Latin and Greek affixes in clinical text. The results show that to a large extent affixes in clinical text are Swedified and that prefixes are used more conservatively than suffixes.

Research Article
Copyright © Nordic Association of Linguistics 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)



Allvin, Helen. 2010. Patientjournalen som genre. En text- och genreanalys om patientjournalers relation till patientdatalagen [The patient record as genre: A text and genre analysis of the relationship of patient records and the patient data act]. Bachelor thesis, Department of Nordic Languages, Stockholm University.Google Scholar
Baayen, R. Harald. 2010. The directed compound graph of English: An exploration of lexical connectivity and its processing consequences. In Olson, Susan (ed.), New Impulses in Word-formation (Linguistische Berichte Sonderheft 17), 383402. Hamburg: Buske.Google Scholar
Banay, George L. 1948. An introduction to medical terminology I: Greek and Latin derivations. Bulletin of the Medical Library Association 36 (1), 127.Google ScholarPubMed
Bretschneider, Claudia, Zillner, Sonja & Hammon, Matthias. 2013. Identifying pathological findings in German radiology reports using a syntacto-semantic parsing approach. In Cohen et al. (eds.), 27–35.Google Scholar
Cohen, K. Bretonnel, Demner-Fushman, Dina, Ananiadou, Sophia, Pestian, John & Tsujii, Junichi (eds.). 2013. Proceedings of the 2013 Workshop on Biomedical Natural Language Processing (BioNLP 2013), 2735. Sofia, Bulgaria: Association for Computational Linguistics.Google Scholar
Dalianis, Hercules, Hassel, Martin, Henriksson, Aron & Skeppstedt, Maria. 2012. Stockholm EPR Corpus: A clinical database used to improve health care. In Nugues, Pierre (ed.), Proceedings of the 4th Swedish Language Technology Conference (SLTC), Lund, 17–18 October, 2526.Google Scholar
Dalianis, Hercules, Hassel, Martin & Velupillai, Sumithra. 2009. The Stockholm EPR Corpus – characteristics and some initial findings. In Bath, Peter A., Petterson, Göran & Steinschaden, Thomas (eds.), Proceedings of ISHIMR 2009. Evaluation and Implementation of E-health and Health Information Initiatives: International Perspectives. 14th International Symposium for Health Information Management Research, Kalmar, Sweden, 243–249.Google Scholar
Fogelberg, Magnus & Petersson, Göran (eds.). 2013. Medicinens språk [The language of medicine]. Stockholm: Liber.Google Scholar
Friedman, Carol, Kra, Pauline & Rzhetsky, Andrey. 2002. Two biomedical sublanguages: A description based on the theories of Zellig Harris. Journal of Biomedical Informatics 35 (4), 222235.CrossRefGoogle ScholarPubMed
Grigonytė, Gintarė, Kvist, Maria, Velupillai, Sumithra & Wirén, Mats. 2014. Improving readability of Swedish Electronic Health Records through lexical simplification: First results. In Williams, Sandra, Siddharthan, Advaith & Nenkova, Ani (eds.), Proceedings of the 3rd Workshop on Predicting and Improving Text Readability for Target Reader Populations (PITR), Association for Computational Linguistics, 7483.Google Scholar
Hagège, Caroline, Marchal, Pierre, Gicquel, Quentin, Darmoni, Stefan, Pereira, Suzanne & Metzger, Marie-Hélène. 2011. Linguistic and temporal processing for discovering hospital acquired infection from patient records. In Riano, David, ten Teije, Annete, Miksch, Silvia & Peleg, Mor (eds.), Proceedings of the ECAI 2010 Conference on Knowledge Representation for Healthcare, KR4HC’10, 7084. Berlin & Heidelberg: Springer.Google Scholar
Hay, Jennifer B. & Plag, Ingo. 2004. What constrains possible suffix combinations? On the interaction of grammatical and processing restrictions in derivational morphology. Natural Language & Linguistic Theory 22, 565596.CrossRefGoogle Scholar
Henriksson, Aron, Hassel, Martin & Kvist, Maria. 2011. Diagnosis code assignment support using random indexing of patient records – a qualitative feasibility study. In Peleg, Mor, Lavrac, Nada & Combi, Carlo (eds.), Proceedings of the 13th Conference on Artificial Intelligence in Medicine (AIME), Bled, Slovenia, 348352.CrossRefGoogle Scholar
Kokkinakis, Dimitrios. 2011a. What is the coverage of SNOMED CT on scientific medical corpora? In Moen, Anne, Andersen, Stig Kjær, Aarts, Jos & Hurlen, Petter (eds.), Procedings of XXIII International Conference of the European Federation for Medical Informatics, 814818. Amsterdam: IOS Press.Google Scholar
Kokkinakis, Dimitrios. 2011b. Evaluating the coverage of three controlled health vocabularies with focus on findings, signs and symptoms. In Pedersen, Bolette Sandford, Nešpore, Gunta & Skadiņa, Inguna (eds.), The 18th Nordic Conference of Computational Linguistics (NODALIDA) (NEALT Proceedings Series12), 27–31.Google Scholar
Kokkinakis, Dimitrios. 2012. The journal of the Swedish Medical Association – a corpus resource for biomedical text mining in Swedish. In Ananiadou, Sophia, Cohen, K. Bretonnel, Demner-Fushman, Dina & Thompson, Paul (eds.), The Third Workshop on Building and Evaluating Resources for Biomedical Text Mining (BioTxtM), an LREC Workshop, Turkey, 4044.Google Scholar
Kurimo, Mikko, Virpioja, Sami, Turunen, Ville & Lagus, Krista. 2010. Morpho Challenge Competition 2005–2010: Evaluations and results. Proceedings of the 11th Meeting of the ACL Special Interest Group on Computational Morphology and Phonology, Association for Computational Linguistics, 8795.Google Scholar
Kvist, Maria, Skeppstedt, Maria, Velupillai, Sumithra & Dalianis, Hercules. 2011. Modeling human comprehension of Swedish medical records for intelligent access and summarization systems – future vision, a physician's perspective. In Fensli, Rune & Dale, Jan Gunnar (eds.), Proceedings of Scandinavian Health Informatics Meeting, 31–35.Google Scholar
Kvist, Maria & Velupillai, Sumithra. 2014. SCAN: A Swedish Clinical Abbreviation Normalizer. Further development and adaptation to radiology. In Kanoulas, Evangelos, Lupu, Mihai, Clough, Paul, Sanderson, Mark, Hall, Mark, Hanbury, Allan & Toms, Elaine (eds.), Proceedings from Conference and Labs of the Evaluation Forum (CLEF 2014) (Lecture Notes in Computer Science 8685), Sheffield, UK, September 2014, 6273.Google Scholar
Laippala, Veronika, Ginter, Filip, Pyysalo, Sampo & Salakoski, Tapio. 2009. Towards automated processing of clinical Finnish: Sublanguage analysis and a rule-based parser. International Journal of Medical Informatics 78:e7e12.CrossRefGoogle Scholar
Nilsson, Inga. 2007. Medicinsk dokumentation genom tiderna: En studie av den svenska patientjournalens utveckling under 1700-talet, 1800-talet och 1900-talet [Medical documentation though time: A study of the Swedish patient record development during the 18th, 19th and 20th century] (Enheten för medicinens historia). Lund: Medical Faculty, Lund University.Google Scholar
NST Dictionary. 2007. Nasjonalbiblioteket. (accessed 17 October 2014).Google Scholar
Nyman, Hans. 2013a. Latinet och svenskan [Latin and Swedish]. In Fogelberg & Petersson (eds.), 42–47.Google Scholar
Nyman, Hans. 2013b. Övriga latinska morfem och vanliga fraser [Additional Latin morphemes and common phrases]. In Fogelberg & Petersson (eds.), 100–106.Google Scholar
Nyman, Hans. 2013c. Grekiskan [Greek]. In Fogelberg & Petersson (eds.), 107–120.Google Scholar
Nyman, Hans. 2013d. Prefix [Prefixes]. In Fogelberg & Petersson (eds.), 121–128.Google Scholar
Östling, Robert. 2013. Stagger: An open-source part of speech tagger for Swedish. Northern European Journal of Language Technology 3, 118. [Linköping: Linköping University Electronic Press]Google Scholar
Patterson, Olga & Hurdle, John F.. 2011. Document clustering of clinical narratives: A systematic study of clinical sublanguages. American Medical Informatics Association Annual Proceedings 2011, 1099–1107.Google Scholar
Skeppstedt, Maria. 2013. Adapting a parser to clinical text by simple pre-processing rules. In Cohen et al. (eds.), 98–101.Google Scholar
Skeppstedt, Maria, Kvist, Maria & Dalianis, Hercules. 2012. Rule-based entity recognition and coverage of SNOMED CT in Swedish clinical text. In Calzolari, Nicoletta, Choukri, Khalid, Declerck, Thierry, Doğan, Mehmet Uğur, Maegaard, Bente, Mariani, Joseph, Moreno, Asuncion, Odijk, Jan & Piperidis, Stelios (eds.), Proceedings of the Eighth International Conference on Language Resources and Evaluation, LREC2012, 1250–1257.Google Scholar
Smedby, Björn. 1991. Medicinens Språk: språket i sjukdomsklassifikationen – mer konsekvent försvenskning eftersträvas [Language of medicine: The language of diagnose classification. More consistent Swedification sought]. Läkartidningen 88 (16), 15191520.Google Scholar
Smedby, Björn. 2013. Klassifikationer och kodverk [Classifications and coding]. In Fogelberg & Petersson (eds.), 180–189.Google Scholar
Smith, Kelly, Megyesi, Beata, Velupillai, Sumithra & Kvist, Maria. 2014. Professional language in Swedish clinical text: Linguistic characterization and comparative studies. Nordic Journal of Linguistics 37 (2), 297323.CrossRefGoogle Scholar
Socialdepartementet. 2008. Patientdatalagen [Patient data act]. Svensk författningssamling 2008:355, with changes 2014:829.Google Scholar
Surján, György & Héja, Gergely. 2003. About the language of Hungarian discharge reports. Studies in Health Technology and Informatics 95, 869873.Google ScholarPubMed
Tanushi, Hideyuki, Kvist, Maria & Sparrelid, Elda. 2014. Detection of healthcare-associated urinary tract infection in Swedish Electronic Health Records. In Grana, Manuel, Toro, Carlos, Howlett, Robert J. & Jain, Lakhmi C. (eds.), Studies in Health Technology and Informatics 207, 330339.Google ScholarPubMed
Temnikova, Irina P., Nikolova, Ivelina, Baumgartner, William A. Jr., Angelova, Galia & Cohen, K. Bretonnel. 2013. Closure properties of Bulgarian clinical text. In Angelova, Galia, Bontcheva, Kalina & Mitkov, Ruslan (eds.), Recent Advances in Natural Language Processing, 667–675. Amsterdam: John Benjamins.Google Scholar
Van Hoof, Henri. 1998. The language of medicine: A comparative ministudy of English and French. In Fischbach, Henry (ed.), Translation and medicine, 4965. Amsterdam: John Benjamins.CrossRefGoogle Scholar
Xu, Hua, Stetson, Peter D. & Friedman, Carol. 2007. A study of abbreviations in clinical notes. In Teich, Jonathan M., Hripcsak, George & Suermondt, Jaap (eds.), American Medical Informatics Association Annual Proceedings 2007, 821–825.Google Scholar
Zeng, Qing T., Redd, Doug, Divita, Guy, Jarad, Samah, Brandt, Cynthia & Nebeker, Jonathan R.. 2011. Characterizing clinical text and sublanguage: A case study of the VA clinical notes. Journal of Health & Medical Informatics 2011:S3.Google Scholar