A comprehensive review of the methods of diagnosing and predicting liver diseases using smart methods

Abstract Liver diseases are among the most significant health problems for humanity, and quick and accurate diagnosis is essential for effective treatment. Nowadays, machine learning and artificial intelligence algorithms play an important role in enhancing the accuracy of diagnosing and predicting these diseases. The aim of this study is to systematically review the intelligent methods used in the diagnosis and prediction of liver diseases. First, the types of liver diseases and the importance of their early diagnosis are introduced, followed by a review of algorithms and the categorization of machine learning and artificial intelligence methods in this field. The application of medical data and liver images for training and evaluating these algorithms is also examined in detail, and the criteria for selecting the optimal diagnostic method are explained. In the end, the results and effectiveness of various approaches are compared, and suggestions for enhancing future research are provided. This article can serve as a comprehensive and practical reference for researchers in the field of intelligent diagnosis of liver diseases.