FP Test is a method for diagnosing the stage of liver fibrosis and the degree of activity of chronic hepatitis according to the results of blood tests.
The method is a machine learning model based on an artificial neural network that accepts the following clinical and laboratory parameters: gender, age, height and weight of the patient, as well as platelet count, levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST) and gamma-glutamyltranspeptidases (GGT).
The “gold standard” for diagnosing the stage of fibrosis, cirrhosis and the degree of activity of chronic hepatitis is a pathomorphological study of liver biopsy.
The accuracy of the method for the diagnosis of stage 3-4 liver fibrosis in comparison with a liver biopsy is 79% (Sens = 70%, Spec = 87%).
The accuracy of the method for diagnosing moderate or severe hepatitis activity compared with liver biopsy is 79% (Sens = 78%, Spec = 80%).