A Data Mining Approach to Prediction of Liver Diseases. (April 2020)

• Record Type: Journal Article
• Authors: Razali, Nazim; Mustapha, Aida; Wahab, Mohd Helmy Abd; Mostafa, Salama A; Rostam, Siti Khadijah
• Is Part Of: Journal of physics. Volume 1529:Number 3(2020)
• Publication Date: 2020-04
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1529/3/032002
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: One of the major diseases in the world is liver disease. The liver is an important part of the large organs in the human body and is also considered a gland. This is because it creates and bites bile. Liver disease is a liver problem that causes the disease. The objective of this study is to propose a rule-based classification model with basic decision making techniques to predict various types of heart disease. To get better results the experiment was done using a different data mining algorithm compared with previous liver disease predictions. All experiments have been implemented at Azure Machine Learning tool. This paper is about to study the prediction of liver disease to produce better performance accuracy by comparing various mining data classification algorithms.