Prediction of Liver Disease using Machine Learning Algorithms
Samiksha H. Zaveri1, Kamini Solanki2
1Ms. Samiksha H. Zaveri*, MCA, Parul University, Vadodara, India.
2Dr. Kamini Solanki, Ph. D. MCA, Parul University, Vadodara, India.
Manuscript received on June 11, 2020. | Revised Manuscript received on June 22, 2020. | Manuscript published on July 10, 2020. | PP: 57-59 | Volume-9 Issue-9, July 2020 | Retrieval Number: 100.1/ijitee.I6876079920 | DOI: 10.35940/ijitee.I6876.079920
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: There are different machine learning techniques widely used in medical field to diagnosis and to predict the liver disease. To endorse the analysis of high and multi dimensional data in health care industry we have reviewed various research papers in which we have focused on various Data mining methods for making use of data in regard to this we come out with, assessment for chosen research papers. Hence, the Objective of this study is to improve the diagnosis and Prediction of the liver disease with the machine learning algorithms. In our paper we suggested that hybrid of Decision Tree and Navie Bayes can give better result with good accuracy.
Keywords: Decision Tree, Liver Disease, Machine Learning Algorithms, Navie Bayes.
Scope of the Article: Machine Learning