PREDICTING CRITICAL LIVER FAILURE USING SUPERVISED MACHINE LEARNING ANALYSIS

Computer Science and Engineering

The liver's purpose is to filter blood as it circulates through the body, turning nutrients and medications ingested from the digestive system into ready-to-use molecules. The liver also removes poisons and other chemical wastes from the blood and prepares them for excretion. Liver failure occurs in the cells of the liver of an individual. Nowadays, machine learning is used in healthcare systems to forecast illness progression. Data is the most critical prerequisite for artificial intelligence. The freshly obtained dataset of liver failure is utilized to construct a machine learning project for predicting this disease. Pre-processing techniques like univariate and bivariate analysis will be done before giving them to the algorithm. The data is visualized for a better understanding of the features, and a classification model is built based on them. Existing classification Algorithms are applied in the dataset and are compared with each other, based on their performance metrics such as accuracy, F1 score, recall the best one among them is deployed for the web application.

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