Prediction and Analysis of Liver Patient Data

Prediction and Analysis of Liver Patient Data is a project that aims to gain insights into liver diseases and develop a system for predicting the likelihood of liver-related health conditions by using data analysis techniques and predictive modeling. This project examines data from liver patients, focusing on the relationships between a key list of liver enzymes, proteins, age, and gender in order to predict the likelihood of liver disease. In this case, we are constructing a model by employing various machine learning algorithms to find the most accurate model. And connect to a flask-based web application. The user can predict the disease by entering parameters into the web application. The project's goal is to uncover significant indicators and build a predictive model to aid in diagnosing liver diseases and identifying potential risks by exploring patterns and relationships within the data.