Predicting Acute Liver Failure using Supervised Machine Learning Approach

Predicting Acute Liver Failure using Supervised Machine Learning Approach

Mrs.A.Vidhya¹ , R.Jayakumar² , K.N. Gokula krishnan³ , N.A. Johan Sharvin Roy⁴

¹Assistant Professor, Department of Computer Science and Engineering, Jeppiaar Engineering college, Chennai-600119

2,3,4Student of Computer Science and Engineering Department, Jeppiaar Engineering College, Chennai-600119

Abstract — The function of liver is to filter blood that circulates through the body, converting nutrients and drugs absorbed from the digestive tract into ready-to-use chemicals. The liver performs many other important functions, such as removing toxins and other chemical waste products from the blood and readying them for excretion. Liver failure that begins in the cells of your liver. Nowadays machine learning is applied to healthcare system where there is a chance of predicting the disease early. The main necessity of Artificial intelligence is data. The past dataset is collected and that dataset is used to build a machine learning model. The necessary pre-processing techniques are applied like univariate analysis and bivariate analysis are implemented. The data is visualised for better understanding of the features and based on that a classification model is built by using machine learning algorithm and comparison of algorithms are done based on their performance metrics like accuracy, F1 score recall etc.

Keywords—Machine learning algorithm, univariate analysis, bivariate  analysis.