Leveraging Machine Learning for Early Detection and Prevention of Liver Disease Mortality in India

The most common causes of liver illness that results in death in India are alcoholrelated liver disease and viral hepatitis, notably hepatitis B and C. Cirrhosis, liver failure, and hepatocellular cancer can develop as a result of these illnesses and can be fatal. Fatigue, stomachache, edema, and jaundice are typical symptoms. Confusion and bleeding are additional late- stage signs. The prevention of liver disease-related mortality in India can be greatly helped by early detection, hepatitis immunization, and lifestyle changes. There are several factors that contribute to liver disease in India, some of the most important ones being cirrhosis of the liver, chronic hepatitis B and C infections, excessive alcohol intake, and nonalcoholic fatty liver disease (NAFLD). These illnesses can cause serious symptoms like jaundice, exhaustion, abdominal discomfort, and, in more severe cases, liver failure. If left untreated, liver failure can be deadly and frequently results in death. Remarkably, India now reports 268,580 liver-related deaths each year, which constitutes 3.17% of all deaths and represents 18.3% of the 2 million liver-related deaths globally. We used different Machine Learning classification techniques, first we did data cleaning and visualized the data, split the data, standardized the data and applied PCA, performed logistic regression with PCA, logistic regression without PCA, Support Vector Machine, Gradient Boosting Classifier, Decision Tree Classifier, Random Forest Classifier without PCA, Random Forest Classifier with PCA, Random Forest Classifier with Feature Selection, Random Forest Classifier with PCA and Feature Selection.