Application of Biochemical Tests and Machine Learning Techniques to Diagnose and Evaluate Liver Disease

Background: The liver function tests (LFTs) remain one of the most commonly employed clinical measures for the diagnosis of hepatobiliary disease. LFTs sometimes referred to as hepatic panel help to determine the health of liver, monitor the progression of a disease and measure the severity of a disease particularly scarring or cirrhosis of the liver. Aims: In this study, we present a new approach to evaluate the natural progression of liver disease through the assessment of eight biochemical parameters: serum total bilirubin (TB), alanine aminotransferase (ALT), aspartate aminotransferase (AST), Alkaline phosphatase (ALP), total protein (TP), albumin (ALB), albumin/globulin (A/G) ratio, and alpha-fetoprotein (AFP) as well as two machine learning (ML) tools—Random Forest and CART to substantive the outcome. Methods: The…