Open AccessLiver Disease Prediction Using Machine Learning Classification
Author(s) -
Jayakumar Sadhasivam,
Senthil J,
Ganesh R.M,
N Chellapan
Publication year - 2021
Publication title -
webology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.259
H-Index - 18
ISSN - 1735-188X
DOI - 10.14704/web/v18si02/web18293
Subject(s) - disease , damages , liver disease , survivability , medicine , support vector machine , population , intensive care medicine , computer science , machine learning , pathology , environmental health , computer network , political science , law
People have disorder of liver that require medical care at correct time. It is utmost important to find the disease before it elapse the curable stage. Significantly, much of understanding of organ development has arisen from analyses of patients with liver deficiencies. Data mining is beneficial to find the disease at early stage based on the factors that can be gathered by performing test on the patient. Nowadays, around 65 % of the population in India are eating junk foods which minimize the metabolism rate and effect liver in many ways. In recent years, liver disorders have excessively increased and are still considered to be life threatening because it has caused low survivability. Still the patients having liver diseases are increasing and the symptoms of the diseases are difficult to identify. The doctors often failed to identify the symptoms which can cause severe damages to the patient and it requires utmost attention. So, we are applying Medical Data Mining (MDM) for predicting the liver disease by using the historical data and understanding their patterns. Here we are using prediction model i.e. Support Vector Machine (SVM) to achieve the goal.