Skip to main content

Spa-neg: An Approach for Negation Detection in Clinical Text Written in Spanish

Part of the Lecture Notes in Computer Science book series (LNBI,volume 12108)


Electronic health records contain valuable information written in narrative form. A relevant challenge in clinical narrative text is that concepts commonly appear negated. Several proposals have been developed to detect negation in clinical text written in Spanish. Much of these proposals have adapted the Negex algorithm to Spanish, but obtained results indicating lower performance than NegEx implementations in other languages. Moreover, in most of these proposals, the validation process could be improved using a shared test corpus focused on negation in clinical text. This paper proposes Spa-neg, an approach to improve negation detection in clinical text written in Spanish. Spa-neg combines three elements: (i) an exploratory data analysis of how negation is written in the clinical text, (ii) use of regular expressions best adapted to the way in which negation is expressed in Spanish, (iii) experiments, and validation using a shared annotated corpus focused on negation. Our findings suggest that the combination of these elements improves the process of negation detection. The tests performed have shown 92% F-Score using IULA Spanish, an annotated corpus for negation in clinical text.


  • Negation detection
  • Electronic health records
  • Clinical Natural Language Processing

This is a preview of subscription content, access via your institution.

Buying options

USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-030-45385-5_29
  • Chapter length: 15 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
USD   109.00
Price excludes VAT (USA)
  • ISBN: 978-3-030-45385-5
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   149.99
Price excludes VAT (USA)
Fig. 1.
Fig. 2.
Fig. 3.


  1. 1.


  1. Aronson, A.R., Lang, F.M.: An overview of MetaMap: historical perspective and recent advances. J. Am. Med. Inform. Assoc. 17(3), 229–236 (2010).

    CrossRef  PubMed  PubMed Central  Google Scholar 

  2. Ballesteros, M., Francisco, V., Díaz, A., Herrera, J., Gervás, P.: Inferring the scope of negation in biomedical documents. In: Gelbukh, A. (ed.) CICLing 2012, Part I. LNCS, vol. 7181, pp. 363–375. Springer, Heidelberg (2012).

    CrossRef  Google Scholar 

  3. Barigou, B.N., Barigou, F., Atmani, B.: Handling negation to improve information retrieval from French clinical reports. J. E-Learning Knowl. Soc. 14(1), 11–31 (2018).

    CrossRef  Google Scholar 

  4. Budrionis, A., Dalianis, H., Yigzaw, K.Y., Makhlysheva, A., Chomutare, T.: Negation detection in Norwegian medical text: porting a Swedish NegEx to Norwegian. Work in progress (2018)

    Google Scholar 

  5. Chapman, W.W., Bridewell, W., Hanbury, P., Cooper, G.F., Buchanan, B.G.: A simple algorithm for identifying negated findings and diseases in discharge summaries. J. Biomed. Inform. 34(5), 301–310 (2001).

    CAS  CrossRef  PubMed  Google Scholar 

  6. Chapman, W.W., et al.: Extending the NegEx lexicon for multiple languages. Stud. Health Technol. Inform. 192(1–2), 677–681 (2013).

    CrossRef  PubMed  PubMed Central  Google Scholar 

  7. Costumero, R., Lopez, F., Gonzalo-Martín, C., Millan, M., Menasalvas, E.: An approach to detect negation on medical documents in Spanish. In: Ślȩzak, D., Tan, A.-H., Peters, J.F., Schwabe, L. (eds.) BIH 2014. LNCS (LNAI), pp. 366–375. Springer, Cham (2014).

    CrossRef  Google Scholar 

  8. Cruz Díaz, N.P., Maña López, M.J.: Negation and Speculation Detection. Editorial Assistant (2019).

  9. Cruz Díaz, N.P., Maña López, M.J., Vázquez, J.M., Álvarez, V.P.: A machine-learning approach to negation and speculation detection in clinical texts. J. Am. Soc. Inform. Sci. Technol. 63(7), 1398–1410 (2012).

    CAS  CrossRef  Google Scholar 

  10. De Albornoz, J.C., Plaza, L., Diaz, A., Ballesteros, M.: UCM-I: a rule-based syntactic approach for resolving the scope of negation. In: *SEM 2012–1st Joint Conference on Lexical and Computational Semantics, vol. 1, pp. 282–287 (2012)

    Google Scholar 

  11. Donatelli, L.: Cues, scope, and focus: annotating negation in Spanish corpora. In: CEUR Workshop Proceedings, vol. 2174, pp. 29–34 (2018)

    Google Scholar 

  12. Elazhary, H.: NegMiner: an automated tool for mining negations from electronic narrative medical documents. Int. J. Intell. Syst. Appl. 9(4), 14–22 (2017).

    CrossRef  Google Scholar 

  13. GitHub: NegEX-MES: NegEX para textos médicos en ESpanol. (Santamaria, J)

  14. Jiménez-Zafra, S.M., Cruz Díaz, N.P., Morante, R., Martín-Valdivia, M.T.: Neges 2018: workshop on negation in Spanish. Procesamiento de Lenguaje Natural 62, 21–28 (2019).

    CrossRef  Google Scholar 

  15. Koza, W., Filippo, D., Cotik, V., Vanessa, S., Ricardo, M.G.: Automatic detection of negated findings in radiological reports for Spanish language: methodology based on lexicon-grammatical information processing. J. Digit. Imaging 1, 19–29 (2019)

    CrossRef  Google Scholar 

  16. Martí Antonín, M.A., Taulé Delor, M., Nofre, M., Marsó, L., Martín Valdivia, M.T., Jiménez Zafra, S.M.: La negación en español: análisis y tipología de patrones de negación (2016).

  17. Mehrabi, S., et al.: DEEPEN: a negation detection system for clinical text incorporating dependency relation into NegEx. J. Biomed. Inform. 54, 213–219 (2015).

    CrossRef  PubMed  PubMed Central  Google Scholar 

  18. Morante, R., Blanco, E.: SEM 2012 shared task: resolving the scope and focus of negation. In: SEM 2012–1st Joint Conference on Lexical and Computational Semantics, vol. 1, pp. 265–274 (2012)

    Google Scholar 

  19. Névéol, A., Dalianis, H., Velupillai, S., Savova, G., Zweigenbaum, P.: Clinical Natural Language Processing in languages other than English: opportunities and challenges. J. Biomed. Semant. 9(1), 1–13 (2018).

    CrossRef  Google Scholar 

  20. Syntactic methods for negation detection in radiology reports in Spanish. In: Proceedings of the 15th Workshop on Biomedical Natural Language Processing, BioNLP 2016, Berlin, Germany, 12 August 2016 (2016).

  21. Negation detection in clinical reports written in German. In: Proceedings of the 5th Workshop on Building and Evaluating Resources for Biomedical Text Mining (BioTxtM 2016) (2016).

  22. Detecting the scope of negations in clinical notes. In: Proceedings of the Second Italian Conference on Computational Linguistics CLiC-IT 2015 (2016)

    Google Scholar 

  23. Annotating negation in Spanish clinical texts. In: Proceedings of the Workshop Computational Semantics Beyond Events and Roles (2017).

  24. Annotation of negation in the IULA Spanish clinical record corpus. In: Proceedings of the Workshop Computational Semantics Beyond Events and Roles, Valencia, Spain (2017).

  25. Savova, G.K., et al.: Mayo clinical text analysis and knowledge extraction system (cTAKES): architecture, component evaluation and applications. J. Am. Med. Inform. Assoc. 17(5), 507–513 (2010).

    CrossRef  PubMed  PubMed Central  Google Scholar 

  26. Tanushi, H., Dalianis, H., Duneld, M., Kvist, M., Skeppstedt, M., Velupillai, S.: Negation scope delimitation in clinical text using three approaches: NegEx, PyConTextNLP and SynNeg. In: Proceedings of the 19th Nordic Conference of Computational Linguistics (NODALIDA 2013), vol. 1, no. 1, pp. 387–397 (2013)

    Google Scholar 

  27. TIJCAI 2015: negated findings detection in radiology reports in Spanish: an adaptation of NegEx to Spanish (2015)

    Google Scholar 

  28. Velupillai, S., et al.: Using clinical natural language processing for health outcomes research: overview and actionable suggestions for future advances. J. Biomed. Inform. 88, 11–19 (2018).

    CrossRef  PubMed  PubMed Central  Google Scholar 

  29. Vincze, V., Szarvas, G., Farkas, R., Móra, G., Csirik, J.: The BioScope corpus: biomedical texts annotated for uncertainty, negation and their scopes. BMC Bioinform. 9(11), 38–45 (2008).

    CAS  CrossRef  Google Scholar 

Download references


This paper is supported by European Union’s Horizon 2020 research and innovation program under grant agreement No. 727658, project IASIS (Integration and analysis of heterogeneous big data for precision medicine and suggested treatments for different types of patients).

Author information

Authors and Affiliations


Corresponding authors

Correspondence to Oswaldo Solarte-Pabón , Ernestina Menasalvas or Alejandro Rodriguez-González .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Verify currency and authenticity via CrossMark

Cite this paper

Solarte-Pabón, O., Menasalvas, E., Rodriguez-González, A. (2020). Spa-neg: An Approach for Negation Detection in Clinical Text Written in Spanish. In: Rojas, I., Valenzuela, O., Rojas, F., Herrera, L., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2020. Lecture Notes in Computer Science(), vol 12108. Springer, Cham.

Download citation

  • DOI:

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-45384-8

  • Online ISBN: 978-3-030-45385-5

  • eBook Packages: Computer ScienceComputer Science (R0)