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Towards an Automatic Diagnosis System for Acute Abdominal Pain - Support Vector Machines for the Diagnosis of Diverticulitis and Non-specific Abdominal Pain

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.