Author:
Tanwar Neha,Rahman Khandakar Faridar
Abstract
Abstract
There has been a rapid growth in the use of automatic decision-making systems and tools in the medical domain. By using the concepts of big data, deep learning, and machine learning, these systems extract useful information from large medical datasets and help physicians in making accurate and timely decisions regarding predictions and diagnosis of diseases. In this regard, this study provides an extensive review of the progress of applying Artificial Intelligence in forecasting and detecting liver diseases and then summarizes related limitations of the studies followed by future research.
Reference70 articles.
1. A novel machine learning approach for early detection of hepatocellular carcinoma patients;Książek;Cogn. Syst. Res.,2019
2. Data Splitting;Reitermanov,2010
3. {UCI} Machine Learning Repository;Dua,2017
4. A Survey and Compare the Performance of IBM SPSS Modeler and Rapid Miner Software for Predicting Liver Disease by Using Various Data Mining Algorithms;Abdar;Cumhur. Sci. J.,2015
5. Performance analysis of classification algorithms on early detection of liver disease;Abdar;Expert Syst. Appl.,2017
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