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Predict Sepsis Level in Intensive Medicine – Data Mining Approach

  • João M. C. Gonçalves
  • Filipe Portela
  • Manuel Filipe Santos
  • Álvaro Silva
  • José Machado
  • António Abelha
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 206)

Abstract

This paper aims to support doctor’s decision-making on predicting the Sepsis level. Thus, a set of Data Mining (DM) models were developed using prevision techniques and classification models. These models enable a better doctor’s decision having into account the Sepsis level of the patient. The DM models use real data collected from the Intensive Care Unit of the Santo António Hospital, in Oporto, Portugal. Classification DM models were considered to predict sepsis level in a supervised learning approach. The models were induced making use of the following algorithms: Decision Trees, Support Vector Machines and Naïve Bayes classifier. The models were assessed using the Confusion Matrix, associated metrics, and Cross-validation. The analysis of the total error rate, sensitivity, specificity and accuracy were the metrics used to identify the most relevant measures to predict sepsis level. This work demonstrates that it is possible to predict with great accuracy the sepsis level.

Keywords

Data mining Classification Intensive Care Sepsis INTCare 

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References

  1. 1.
    Mador, R.L., Shaw, N.T.: The impact of a Critical Care Information System (CCIS) on time spent charting and in direct patient care by staff in the ICU: a review of the literature. International Journal of Medical Informatics 78, 435–445 (2009)CrossRefGoogle Scholar
  2. 2.
    Häyrinen, K., Saranto, K., Nykänen, P.: Definition, structure, content, use and impacts of electronic health records: A review of the research literature. International Journal of Medical Informatics 77, 291–304 (2008)CrossRefGoogle Scholar
  3. 3.
    Santos, M.F., Portela, F., Vilas-Boas, M., Machado, J., Abelha, A., Neves, J.: INTCARE - Multi-agent approach for real-time Intelligent Decision Support in Intensive Medicine. In: 3rd International Conference on Agents and Artificial Intelligence, Rome, Italy (2011)Google Scholar
  4. 4.
    Gago, P., Santos, M.F., Silva, Á., Cortez, P., Neves, J., Gomes, L.: INTCare: a knowledge discovery based intelligent decision support system for intensive care medicine. Journal of Decision Systems (2006)Google Scholar
  5. 5.
    Portela, F., Santos, M.F., Vilas-Boas, M.: A Pervasive Approach to a Real-Time Intelligent Decision Support System in Intensive Medicine. In: Fred, A., Dietz, J.L.G., Liu, K., Filipe, J. (eds.) IC3K 2010. CCIS, vol. 272, pp. 368–381. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  6. 6.
    Bardram, J.E., Baldus, H., Favela, J.: Pervasive computing in hospitals. Pervasive Computing in Healthcare, 49–77 (2007)Google Scholar
  7. 7.
    Varshney, U.: Pervasive healthcare and wireless health monitoring. Mobile Networks and Applications 12, 113–127 (2007)CrossRefGoogle Scholar
  8. 8.
    Breiman, L., Friedman, J.H., Olshen, R.A., Stone, C.J.: Classification and regression. Wadsworth, Belmont (1984)MATHGoogle Scholar
  9. 9.
    O. D. M. Concepts: 11g Release 1 (11.1), Oracle Corp, vol. 2007 (2005)Google Scholar
  10. 10.
    Tamayo, P., Berger, C., Campos, M., Yarmus, J., Milenova, B., Mozes, A., et al.: Oracle Data Mining. In: Data Mining and Knowledge Discovery Handbook, pp. 1315–1329 (2005)Google Scholar
  11. 11.
    Portela, F., Santos, M.F.: Data Mining Predictive Models for Pervasive Intelligent Decision Support in Intensive Care Medicine. In: Presented at the KMIS 2012 - International Conference on Knowledge Management and Information Sharing, Barcelona (2012)Google Scholar
  12. 12.
    Portela, F., Gago, P., Santos, M.F., Silva, A., Rua, F., Machado, J., et al.: Knowledge Discovery for Pervasive and Real-Time Intelligent Decision Support in Intensive Care Medicine. Presented at the KMIS 2011- International Conference on Knowledge Management and Information Sharing, Paris, France (2011)Google Scholar
  13. 13.
    Portela, F., Santos, M.F., Silva, Á., Machado, J., Abelha, A.: Enabling a Pervasive approach for Intelligent Decision Support in Critical Health Care. Presented at the HCist 2011 – International Workshop on Health and Social Care Information Systems and Technologies, Algarve, Portugal (2011)Google Scholar
  14. 14.
    SSC, Surviving sepsis campaign (2010), http://www.survivingsepsis.org/Introduction/Pages/default.aspx (website accessed on November 24, 2011)
  15. 15.
    Bone, R.C., Balk, R.A., Cerra, F.B., Dellinger, R.P., Fein, A.M., Knaus, W.A., Schein, R.M., Sibbald, W.J.: Definitions for sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. The ACCP/SCCM consensus conference committee. American college of chest physicians/society of critical care medicine. Chest 101(6), 1644–1655 (1992)Google Scholar
  16. 16.
    Guy, W.: ECDEU Assessment Manual for Psychopharmacology: 1976. National Institute of Mental Health (1976)Google Scholar
  17. 17.
    Guy, W.: Clinical global impressions (CGI) scale. Modified from: Rush J., et al. Psychiatric measures (2000)Google Scholar
  18. 18.
    ODM, Binning (discretization) (2012), http://docs.oracle.com (website accessed on September 20, 2012)
  19. 19.
    Dellinger, R.P., Levy, M.M., Carlet, J.M., Bion, J., Parker, M.M., Jaeschke, R., Reinhart, K., Angus, D.C., Brun-Buisson, C., Beale, R., et al.: Surviving sepsis campaign: international guidelines for management of severe sepsis and septic shock: 2008. Intensive Care Medicine 34(1), 17–60 (2008)CrossRefGoogle Scholar
  20. 20.
    Levy, M., Fink, M., Marshall, J., Abraham, E., Angus, D., Cook, D., Cohen, J., Opal, S., Vincent, J., Ramsay, G.: 2001 SCCM/ESICM/ACCP/ATS/SIS international sepsis definitions conference. Critical Care Medicine 31(4), 1250–1256 (2003a) (Special Articles)CrossRefGoogle Scholar
  21. 21.
    Levy, M., Fink, M., Marshall, J., Abraham, E., Angus, D., Cook, D., Cohen, J., Opal, S., Vincent, J., Ramsay, G.: 2001 SCCM/ESICM/ACCP/ATS/SIS international sepsis definitions conference. Intensive Care Medicine 29(4), 530–538 (2003b)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • João M. C. Gonçalves
    • 1
  • Filipe Portela
    • 1
  • Manuel Filipe Santos
    • 1
  • Álvaro Silva
    • 2
  • José Machado
    • 3
  • António Abelha
    • 3
  1. 1.Algoritmi CentreUniversity of MinhoGuimarãesPortugal
  2. 2.Serviço Cuidados IntensivosCentro Hospitalar do PortoPortoPortugal
  3. 3.CCTCUniversity of MinhoBragaPortugal

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