• Dr.R.Rangaraj
• Nibin Mathew

Experiencing liver disease has been quickly expanding because of extreme drinking of liquor; breathing in dirtied gas, drugs, debased food and packing food pickles, so the clinical master framework will assist a specialist with automatic prediction. The liver assumes a vital part in life which upholds the removal of poisons from the body. So early prediction is vital to analyze the disease and recuperate. Various kinds of AI, Unsupervised, and Reinforcement Learning for determination of liver disease, for example, SVM, KNN, K-Mean clustering, neural network, Decision tree and so forth and give different accuracy, precision, sensitivity. The motive of this paper is to give a survey and comparative examination of the whole AI strategies for determination and prediction of liver disease in the clinical region, which has previously been utilized for the prediction of liver disease by different creators and the investigation depend on Accuracy, Sensitivity, Precision, and Specificity.

Liver diagnosis, Machine learning, liver tumor, Unsupervised, Expert System;

"REVIEWED LIVER CANCER PREDICTION USING UNSUPERVISED MACHINE LEARNING ALGORITHMS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 8, page no.b470-b475, August-2022, Available :http://www.jetir.org/papers/JETIR2208158.pdf

"REVIEWED LIVER CANCER PREDICTION USING UNSUPERVISED MACHINE LEARNING ALGORITHMS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 8, page no. ppb470-b475, August-2022, Available at : http://www.jetir.org/papers/JETIR2208158.pdf