Calculation of melatonin and resveratrol effects on steatosis hepatis using soft computing methods

Abstract In this work, beneficial effects of melatonin and resveratrol drugs on liver damage in rats, induced by application of acute and chronic carbon tetrachloride (CCl4 ) have been examined. The study consists of three main stages: (1) Data acquisition: light microscopic images were obtained from 60 rats separated into 10 groups after the preparation of liver tissue samples for histological examination. Rats in first five experimental groups for the four-day and the other five groups for twenty-day were examined. (2) Data processing: by the help of histograms of oriented gradient (HOG) method, obtaining low-dimensional image features (color, shape and texture) and classifying five different group characteristics by using these features with artificial neural networks (ANNs), and support vector machines (SVMs) have been provided. (3) Calculation of drug effectiveness: firstly to determine the differences between group characteristics of rats, a pilot group has been selected (diseased group-CCl4), and the responses of ANN and SVM trained by HOG features have been calculated. As a result of ANN, it has been seen that melatonin and resveratrol drugs have %65.62–%75.12 positive effects at the end of the fourth day, %84.12–%98.89 positive effects on healing steatosis hepatis at the end of the twentieth day respectively and as a result of SVM, it has been seen that melatonin and resveratrol drugs have %62.5–%68.75 positive effects at the end of the fourth day, %45.12–%60.89 positive effects on healing steatosis hepatis at the end of the twentieth day respectively.