TOWARDS AN AUTOMATIC DIAGNOSIS SYSTEM FOR ACUTE ABDOMINAL PAIN - Support Vector Machines for the Diagnosis of Diverticulitis and Non-specific Abdominal Pain

Malin Björnsdotter Åberg, Kajsa Nalin, Lars-Erik Hansson, Helge Malmgren

2009

Abstract

The process of medical diagnosis is highly complex, and automatic decision support systems are appealing. In this study we investigate the feasibility of automating one such decision-making process, namely the diagnosis of patients seeking care for acute abdominal pain, and, specifically the diagnosis of acute diverticulitis. We used a linear support vector machine (SVM) to classify diverticulitis from all other reported cases of abdominal pain and from the important differential diagnosis non-specific abdominal pain (NSAP). Using a database containing 3 337 patients, the SVM obtained results comparable to those of the doctors. The distinction between diverticulitis and non-specific pain was substantially better for the SVM. Here the doctor achieved a sensitivity of 0.714 and a specificity of 0.963. When adjusted to the physicians results, the SVM sensitivity/specificity was higher at 0.714/0.985 and 0.786/0.963 respectively. Age was found as the most important factor for diagnosis, closely followed by C-reactive protein level and various pain indicators on the left hand side. Thus, the support vector machine is a promising tool in the diagnosis of acute abdominal pain.

References

  1. A°berg, M. C., Löken, L., and Wessberg, J. (2008). An evolutionary approach to multivariate feature selection for fMRI pattern analysis. Proceedings of the International Conference on Bio-inspired Systems and Signal Processing.
  2. A°berg, M. C. and Wessberg, J. (2007). Evolutionary optimization of classifiers and features for single trial EEG discrimination. BioMedical Engineering Online, 6(32).
  3. Adams, I. D., Chan, M., Clifford, P. C., Cooke, W. M., Dallos, V., de Dombal, F. T., Edwards, M. H., Hancock, D. M., Hewett, D. J., and McIntyre, N. (1986). Computer aided diagnosis of acute abdominal pain: a multicentre study. British Medical Journal (Clinical research ed.), 293(6550):800-804.
  4. Ambrosetti, P., Robert, J., Witzig, J., Mirescu, D., Mathey, P., Borst, F., and Rohner, A. (1994). Acute left colonic diverticulitis: a prospective analysis of 226 consecutive cases. Surgery, 115(5):546-50.
  5. Bellman, R. E. (1961). Adaptive Control Processes. Princeton University Press, Princeton, NJ.
  6. Blum, A. and Langley, P. (1997). Selection of relevant features and examples in machine learning. Artificial Intelligence, 97(1-2):245-271.
  7. Chawla, N., Bowyer, K., Hall, L., and Kegelmeyer, W. (2002). Smote: synthetic minority over-sampling technique. Journal of Artificial Intelligence Research, 16:321357.
  8. de Dombal, F., Leaper, D., Staniland, J., McCann, A., and Horrocks, J. (1972). Computer-aided diagnosis of acute abdominal pain. British Medical Journal, 2(5804):9-13.
  9. Ferzoco, L., Raptopoulos, V., and Silen, W. (1998). Acute diverticulitis. The New England Journal of Medicine, 338(21):1521-6.
  10. Hansson, L.-E. (2002). Akut Buk. Lund: Studentlitteratur.
  11. Laurell, H., Hansson, L., and Gunnarsson, U. (2006). Acute abdominal pain among elderly patients. Gerontology, 52(6):339-44.
  12. Laurell, H., Hansson, L., and Gunnarsson, U. (2007). Acute diverticulitis clinical presentation and differential diagnostics. Colorectal Disease, 6(9):496-501.
  13. Marchiori, E., Moore, J. H., and Rajapakse, J. C., editors (2007). A Genetic Embedded Approach for Gene Selection and Classification of Microarray Data, volume 4447 of Lecture Notes in Computer Science. Springer.
  14. Nalin, K. (2006). Den ideala kliniska beslutsprocessen. en studie av arbetsprocessen p en kirurgisk akutmottagning/The ideal clinical decison process. a study of the work process in an acute surgical ward. in swedish. masters thesis. Masters thesis in Cognitive Science, University of Gothenburg.
  15. Suykens, J., Gestel, T. V., Brabanter, J. D., Moor, B. D., and Vandewalle, J. (2002). Least Squares Support Vector Machines. World Scientific.
  16. Young-Fadok, T., Roberts, P., Spencer, M., and BG, W. (2000). Colonic diverticular disease. Current Problems in Surgery, (37):459514.
Download


Paper Citation


in Harvard Style

Björnsdotter Åberg M., Nalin K., Hansson L. and Malmgren H. (2009). TOWARDS AN AUTOMATIC DIAGNOSIS SYSTEM FOR ACUTE ABDOMINAL PAIN - Support Vector Machines for the Diagnosis of Diverticulitis and Non-specific Abdominal Pain . In Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2009) ISBN 978-989-8111-63-0, pages 51-57. DOI: 10.5220/0001546200510057


in Bibtex Style

@conference{healthinf09,
author={Malin Björnsdotter Åberg and Kajsa Nalin and Lars-Erik Hansson and Helge Malmgren},
title={TOWARDS AN AUTOMATIC DIAGNOSIS SYSTEM FOR ACUTE ABDOMINAL PAIN - Support Vector Machines for the Diagnosis of Diverticulitis and Non-specific Abdominal Pain},
booktitle={Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2009)},
year={2009},
pages={51-57},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001546200510057},
isbn={978-989-8111-63-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2009)
TI - TOWARDS AN AUTOMATIC DIAGNOSIS SYSTEM FOR ACUTE ABDOMINAL PAIN - Support Vector Machines for the Diagnosis of Diverticulitis and Non-specific Abdominal Pain
SN - 978-989-8111-63-0
AU - Björnsdotter Åberg M.
AU - Nalin K.
AU - Hansson L.
AU - Malmgren H.
PY - 2009
SP - 51
EP - 57
DO - 10.5220/0001546200510057