Prediction of Liver Diseases using Decision Trees and Machine Learning Algorithms

Abstract

Human body consists of various important organs for processing the entire metabolism of the human being. Some of them are the kidneys, brain, heart and liver. The proper functioning of these organs will lead the person happy life. The identification of problems to these organs is also important at the right point of time. In the current article a GUI model had been developed such that to identify the level of damage happened to liver based on the data given by users. The current model will also provide the details about various problems that causes to the liver through GUI model. The saying in the medical field is always predicting the disease in earlier stages is better than at the crucial period such that to reduce the damage of that problem to that particular organ. The symptoms also become more different and also difficult to analyze at later stages. In the current tool, an attempt had been made to utilize the machine learning algorithms like K-means, ANN and SVM to analyze the liver patients from a group of normal patients. The comparison of the machine learning algorithms for their performance to identify the liver problems based on performance factors also observed. The developed GUI can be a good source for the doctors to analyze liver diseases.