title: Analyses of a cirrhotic patient's evolution using self organizing mapping and Child-Pugh scoring.
abstract: Due to the importance of cirrhosis evolution, this study examined cirrhotic patients using Self Organizing Mapping (SOM) based on the Child-Pugh scoring method. Because Colored Doppler Ultrasound (CDU) has too many parameters, scoring can be a very difficult task. Classifying cirrhotic patients via SOM and investigating weights of the cirrhotic CDU parameters are aimed in this study. SOM was used to map high dimensional cirrhotic data onto two dimensional clustered data. These clusters provided a feature map of cirrhotic patients. In this study, 103 cirrhotic patients and a control group of 44 healthy individuals were examined in the hospital, and parameters were analyzed using SOM. These data were obtained using CDU, and age and sex parameters were analyzed in this study. Cirrhotic patients were histopathologically separated into subgroups using the Child-Pugh scoring method, and the presence of ascites was determined using SOM. In this study, differences between the control group and cirrhotic patients with their subgroups were investigated using SOM, and the results were discussed. Renal artery indices, hepatic artery indices, portal vein parameters, age and the degree of ascites were analyzed using SOM for a total of 147 individuals. The combination of SOM and Child-Pugh scoring method can be useful for the interpretation of cirrhotic patient's evolution. Computer-based SOM algorithm and negative effectiveness of a large scale dataset could be minimized by adjusting the weight of the parameters. This study will faciliate doctors to make better decisions for their patients.
authors: Radiodiagnostic Department, Fırat University Faculty of Medicine, Rectorate Campus, 23119, Elazığ, Turkey.
authors: Selami
authors: S
authors: Serhatlıoğlu
authors: Fırat
authors: F
authors: Hardalaç
authors: Uğurhan
authors: U
authors: Kutbay
authors: Özgür
authors: Ö
authors: Kocaöz
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D005260:Female; D006801:Humans; D008103:Liver Cirrhosis / Q000000981:diagnostic imaging* / Q000473:pathology*; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer; D012737:Sex Factors; D018615:Ultrasonography, Doppler, Color
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