AI-Powered Automated Methods for Predicting Liver Disease: A Recent Review

The diagnosis of liver disease using invasive method is a major concern for people. The invasive method like biopsy may be the last decision of doctors after many non-invasive methods like ultrasound sonography, clinical predictive score or elastography may be etc. The early detection of liver disease helps doctors to start the proper treatment in early stages. The artificial intelligence can be integrated into non-invasive diagnostic methods to improve the diagnosis in early stages. This study focuses on the systematic review of studies of AI based diagnosis of liver diseases in recent years since 2018. There is a good potential for the diagnosis of liver diseases using AI-assisted systems. The study’s comparative analysis revealed that different AI algorithms are applied by researchers on clinical data and image data from scanning tests. The purpose of this study is to find the new direction of research in diagnosis of the liver disease in early stages. This study emphasized on an AI techniques on variety of liver diseases such as distinguishing between normal and infected liver, fatty liver, non-alcoholic fatty liver, measurement of fibrosis, advancement of 0 etc.