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Authors: Malin Björnsdotter Åberg 1 ; Kajsa Nalin 2 ; Lars-Erik Hansson 3 and Helge Malmgren 3

Affiliations: 1 University of Gothenburg, Sweden ; 2 Centre of Interdisciplinary Research/Cognition/Information, Sweden ; 3 Department of Surgery, Sahlgrenska University Hospital/Östra, Sweden

Keyword(s): Support vector machines, computer-aided diagnostics, acute abdominal pain.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Expert Systems ; Health Information Systems ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Support for Clinical Decision-Making ; Symbolic Systems

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. (More)

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Paper citation in several formats:
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 (BIOSTEC 2009) - HEALTHINF; ISBN 978-989-8111-63-0; ISSN 2184-4305, SciTePress, pages 51-57. DOI: 10.5220/0001546200510057

@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 (BIOSTEC 2009) - HEALTHINF},
year={2009},
pages={51-57},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001546200510057},
isbn={978-989-8111-63-0},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the International Conference on Health Informatics (BIOSTEC 2009) - HEALTHINF
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
IS - 2184-4305
AU - Björnsdotter Åberg, M.
AU - Nalin, K.
AU - Hansson, L.
AU - Malmgren, H.
PY - 2009
SP - 51
EP - 57
DO - 10.5220/0001546200510057
PB - SciTePress