FateForecast

"FateForecast" is a predictive modeling project focused on using Bayesian estimation techniques to forecast mortality risk in heart failure patients.

Introduction

Heart failure is a critical health issue worldwide, leading to significant mortality rates. Traditional predictive models often overlook individual variabilities and uncertainties present in medical data. "FateForecast" aims to address these challenges by developing a Bayesian predictive model for mortality risk in heart failure patients.

Features

Predicts mortality risk in heart failure patients using Bayesian estimation techniques.
Incorporates prior clinical knowledge and probabilistic understanding of patient outcomes.
Provides insights into the uncertainties and relative importance of different predictors in heart failure outcomes.

Installation

Clone the repository:

git clone https://github.com/yourusername/FateForecast.git

Navigate to the project directory:
```
cd FateForecast
```
Install the required dependencies:
```
pip install -r requirements.txt
```

Usage

Ensure you have Jupyter Notebook installed on your system.
Open the fate_forecast.ipynb notebook using Jupyter Notebook.
Follow the instructions and execute the cells to run the project.

Dataset

The dataset used in this project comprises records of 368 patients who visited a cardiology hospital in Pakistan, with symptoms indicative of heart failure. It includes 60 quantitative parameters for each patient, such as age, smoking status, mortality during the hospital visit, and maximum heart rate achieved, among others. The dataset's diversity in variables allows for a detailed and nuanced modeling approach.

Contributors

Akshit
Daniil Serpukhov
Sourabh Kumar

License

This project is licensed under the MIT License. See the LICENSE file for details.

Show Your Support

If you find "FateForecast" helpful, consider giving it a star ⭐️ on GitHub! Your support is greatly appreciated.

Sourabh-Kumar7/FateForecast