Volume 20 No 22 (2022)
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Applying Machine Learning Techniques in Liver Disease Detection: A Comprehensive Review
Aman Kumar, Dr. Randeep Singh
Abstract
Machine learning makes use of artificial intelligence to create prediction models more quickly and effectively than traditional approaches by finding hidden patterns in massive amounts of data. With this in mind, these techniques can be used in a number of hepatology-related contexts. In this review, we look at the literature on machine learning in hepatology and the early diagnosis of liver illness. We give a general review of the benefits and drawbacks of machine learning techniques and discuss possible uses for them in liver disease prediction. We predict that the clinical practice of liver disease diagnosis will alter as a result of the application of ML techniques to produce prediction algorithms. Early detection of liver illness allows for timely diagnosis and, in some cases, a full recovery. The information in this review will give readers the chance to become more knowledgeable about the available machine learning (ML) techniques and their possible applications to liver diseases related problems.
Keywords
Data Mining, Liver diseases, Machine learning, Classification, Feature Selection
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