A novel model based on non invasive methods for prediction of liver fibrosis

Serial liver biopsies are typically the gold standard for diagnosis of liver fibrosis progression. However, It is associated with serious complications, inconvenient to patients and expensive, the challenge is to substitute the liver biopsy with non-invasive method. The proposed technique is employed to resolve this issue with average accuracy 99.48% for 5-folds cross validation. This accuracy pave the way to utilize classification models as a clinically non-invasive and reliable method to assess the degree of liver fibrosis.