• Mrs. Veena Potdar
• Mrs. Lavanya Santhosh
• Kruthika Mannur
• Rijuta D
• Varshitha S,Sudhanva K S

Abstract - Since the inception of civilization, human beings have been the target of the effects of substances on the liver. The liver is one of the most important organs, being responsible for creating nutrients, metabolizing them and maintaining a non-toxic body condition. One of the most common types of liver disease is fatty liver disease. Fatty liver disease is one of the most dangerous human diseases and has a very serious impact on human life. Liver disease is also called by the name hepatic disease. It damages the liver. Some symptoms of liver disease may include weight loss and jaundice, and there are some different forms of liver disease. There are two different kinds of liver diseases. It is an alcoholic fatty liver disease that develops in people who consume a lot of alcohol. It results in damage to the liver and leads to cirrhosis. Non-alcohol fatty liver is one of the leading causes of liver disease worldwide. They accumulate fat in our liver. Human life can be saved by the detection of liver disease in its early stages. Data mining has become an easy method for liver disease prediction. The research being done to predict liver disease has a lot of challenging tasks. It is calculated from medical databases. To overcome this, research data mining techniques such as regression problems and classification are used. We can classify patients’ risk levels by using data mining techniques. It predicts liver disease accurately and efficiently by using machine learning algorithms.

"Liver Disease Prediction using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 7, page no.e509-e516, July-2022, Available :http://www.jetir.org/papers/JETIR2207463.pdf

"Liver Disease Prediction using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 7, page no. ppe509-e516, July-2022, Available at : http://www.jetir.org/papers/JETIR2207463.pdf