Abstract
This study explores the feasibility of a decision-support system for patients seeking care for acute abdominal pain, and, specifically the diagnosis of acute diverticulitis. We used a linear support vector machine (SVM) to separate diverticulitis from all other reported cases of abdominal pain and from the important differential diagnosis non-specific abdominal pain (NSAP). On a database containing 3337 patients, the SVM obtained results comparable to those of the doctors in separating diverticulitis or NSAP from the remaining diseases. The distinction between diverticulitis and NSAP was, however, substantially improved by the SVM. For this patient group, the doctors 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 discriminative variable, closely followed by C-reactive protein level and lower left side pain.
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References
Nalin, K.: Den ideala kliniska beslutsprocessen. en studie av arbetsprocessen på en kirurgisk akutmottagning/The ideal clinical decison process. A study of the work process in an acute surgical ward. Masters thesis in Cognitive Science, University of Gothenburg (2006)
Hansson, L.E.: Akut Buk. Studentlitteratur, Lund (2002)
de Dombal, F., Leaper, D., Staniland, J., McCann, A., Horrocks, J.: Computer-aided diagnosis of acute abdominal pain. British Medical Journal 2(5804), 9–13 (1972)
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., McIntyre, N.: Computer aided diagnosis of acute abdominal pain: a multicentre study. British Medical Journal (Clinical research ed.) 293(6550), 800–804 (1986)
Bellman, R.E.: Adaptive Control Processes. Princeton University Press, Princeton (1961)
Ambrosetti, P., Robert, J., Witzig, J., Mirescu, D., Mathey, P., Borst, F., Rohner, A.: Acute left colonic diverticulitis: a prospective analysis of 226 consecutive cases. Surgery 115(5), 546–550 (1994)
Ferzoco, L., Raptopoulos, V., Silen, W.: Acute diverticulitis. The New England Journal of Medicine 338(21), 1521–1526 (1998)
Young-Fadok, T., Roberts, P., Spencer, M., Wolff, B.G.: Colonic diverticular disease. Current Problems in Surgery (37), 459–514 (2000)
Laurell, H., Hansson, L., Gunnarsson, U.: Acute abdominal pain among elderly patients. Gerontology 52(6), 339–344 (2006)
Laurell, H., Hansson, L., Gunnarsson, U.: Acute diverticulitis – clinical presentation and differential diagnostics. Colorectal Disease 6(9), 496–501 (2007)
Suykens, J., Gestel, T.V., Brabanter, J.D., Moor, B.D., Vandewalle, J.: Least Squares Support Vector Machines. World Scientific, Singapore (2002)
Blum, A., Langley, P.: Selection of relevant features and examples in machine learning. Artificial Intelligence 97(1-2), 245–271 (1997)
Chawla, N., Bowyer, K., Hall, L., Kegelmeyer, W.: Smote: synthetic minority over-sampling technique. Journal of Artificial Intelligence Research 16, 321–357 (2002)
Hernandez Hernandez, J.C., Duval, B., Hao, J.-K.: A genetic embedded approach for gene selection and classification of microarray data. In: Marchiori, E., Moore, J.H., Rajapakse, J.C. (eds.) EvoBIO 2007. LNCS, vol. 4447, pp. 90–101. Springer, Heidelberg (2007)
Åberg, M., Löken, L., Wessberg, J.: An evolutionary approach to multivariate feature selection for fMRI pattern analysis. In: Encarnação, P., Veloso, A. (eds.) Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing (BIOSIGNALS), Funchal, Madeira, Portugal, pp. 302–307. INSTICC Press (2008)
Björnsdotter Åberg, M., Wessberg, J.: An evolutionary approach to the identification of informative voxel clusters for brain state discrimination. IEEE Journal of Selected Topics in Signal Processing 2(6), 919–928 (2008)
Åberg, M.C., Wessberg, J.: Evolutionary optimization of classifiers and features for single trial EEG discrimination. BioMedical Engineering Online 6(32) (2007)
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Björnsdotter, M., Nalin, K., Hansson, LE., Malmgren, H. (2010). Support Vector Machine Diagnosis of Acute Abdominal Pain. In: Fred, A., Filipe, J., Gamboa, H. (eds) Biomedical Engineering Systems and Technologies. BIOSTEC 2009. Communications in Computer and Information Science, vol 52. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11721-3_27
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DOI: https://doi.org/10.1007/978-3-642-11721-3_27
Publisher Name: Springer, Berlin, Heidelberg
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