Prognosis of Liver Disorders in Dna Positive Hbv Patients Based on Fuzzy Soft Sets

Abstract

Liver disease and disorders are serious public health burdens because of the high prevalence among populations worldwide and poor long-term clinical outcome. The outcomes of the disease include deaths from liver decompensation, cirrhosis and HCC. Many liver diseases, including chronic HBV and HCV infection, ALD, NAFLD, autoimmune liver disease and drug-induced liver disease (DILI), potentially threaten a large proportion of the global population. The fuzzy soft set principle theory has been used for the developing of a diagnostic system in medicine and devise a prediction system named as fuzzy soft expert system which is a rule-based system uses fuzzy set and fuzzy soft set. There are five main components included in the basic structure, they are: (1) A fuzzication that translates the inputs (real-values) into fuzzy values, (2) obtaining fuzzy sets, (3) changing in to fuzzy soft sets, (4) reduction of normal parameter of fuzzy soft sets, (5) output data by algorithm. Fifty two individuals suspected and managed as HBV patients were involved in this study.All of them were attending liver diseases unit at Azadi teaching hospital in Duhok, Kurdistan Region-Iraq. They were being managed by the herpetology specialist as HBV infected patients. Their parameters (Alanine Aminotransferase (ALT), Aspartate aminotransferase (AST), Total Serum Albumin (Alb.), and Total Serum Bilirubin (T.S.Bil.)), were used as input data and the score of each patient was calculated. The developed fuzzy soft expert system was used to obtain the score for each as prognostic model for liver disorders. The score of 10 of those patients are selected and compared with the clinical status of each base on signs and symptoms of the HBV infection. Score more than 101.844 was considered to be highly linked with HBV infection. Scores less than 101.844 was considered to be not related to HBV infection.