Aim:The aim was to develop a high-performance computer-aided diagnosis (CAD) system with image processing and pattern recognition in diagnosing pancreatic cancer by using endosonography images.Materials and Methods:On the images, regions of interest (ROI) of three groups of patients (<40, 40-60 and >60) were extracted by experts; features were obtained from images using three different techniques and were trained separately for each age group with an Artificial Neural Network (ANN) to diagnose cancer. The study was conducted on endosonography images of 202 patients with pancreatic cancer and 130 noncancer patients.Results:122 features were identified from the 332 endosonography images obtained in the study, and the 20 most appropriate features were selected by using the relief method. Images classified under three age groups (in years; <40, 40-60 and >60) were tested via 200 random tests and the following ratios were obtained in the classification: accuracy: 92%, 88.5%, and 91.7%, respectively; sensitivity: 87.5%, 85.7%, and 93.3%, respectively; and specificity: 94.1%, 91.7%, and 88.9%, respectively. When all the age groups were assessed together, the following values were obtained: accuracy: 87.5%, sensitivity: 83.3%, and specificity: 93.3%.Conclusions:It was observed that the CAD system developed in the study performed better in diagnosing pancreatic cancer images based on classification by patient age compared to diagnosis without classification. Therefore, it is imperative to take patient age into consideration to ensure higher performance.

Helicobacter pylori infection and diabetes mellitus are two independent common diseases. It is showed that the worsening glycemic and metabolic control increases the rates of Helicobacter pylori infections and Helicobacter pylori is shown as one of the common problems in diabetic patients with complaints of gastrointestinal diseases. In this study, we aimed to investigate the prevalence and eradication rates of Helicobacter pylori in diabetic patients and the relationship of Helicobacter pylori with the risk factors and diabetic complications. In our study, in which we have included 133 patients, we have shown a significant relationship between Helicobacter pylori infections and metabolic syndrome, insulin resistance, inflammations, and diabetic complications.

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The short-term results of SRS are promising. The forthcoming new-generation devices and increasing experience may further improve efficacy and decrease untoward effects.

Background/aims: Tuberculous peritonitis is prevalent in developing countries and its diagnosis is