An Efficient Model for Predicting Liver Disease Using Machine Learning

Liver Diseases account for more than 2.8% of Indian adult deaths each year. The major issue with finding out the liver disease is difficulty in diagnosing its early stages which will be showing subtle symptoms. Mostly the liver disease will show its symptoms only in the advanced stage, which causes difficulty in identification and diagnosing. This article looks to improve diagnosis methods for liver diseases identification by verifying different patient parameters and their respective genome expression. This paper also analyzes the various computational algorithms that can be used in the above-mentioned methodologies to find out the best models. It also proposes various methods to improve the efficiency of these algorithms.