Healthcare Billing Amount Prediction

This project aims to predict hospital billing amounts based on patient data using supervised learning algorithms.

The project focuses on analyzing healthcare data to estimate hospital billing amounts by leveraging machine learning techniques. Patient demographic information, medical conditions, hospitalization details, and billing-related features are used to train predictive models.

Project Overview

In this project, multiple regression models were evaluated to predict hospital billing amounts. Linear Regression and Decision Tree Regressor were tested, and the Decision Tree model was selected due to its superior performance. The final model was optimized using GridSearchCV and evaluated with metrics such as MAE, RMSE, and R² score.