Skip to content

darshjoshi/heart_failure_prediction

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

19 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Heart Failure Prediction: A mock project for Kaiser Permenente Hospital

This repository contains a project made for academic progression for the subject Practical Data Science (CS667) at Pace University.

Guided by: Professor Stephanie Langelend

Executive Summary

To enhance patient care and preemptively identify at-risk individuals, the team has developed a sophisticated predictive model for heart failure, tailored specifically for the patient demographics of the Kaiser Permanente hospital chain. Utilizing state-of-the-art machine learning techniques and the rich medical datasets available, our model aims to provide clinicians with a powerful tool to assess heart failure risks, enabling timely interventions and optimizing resource allocation, ultimately driving better patient outcomes and reducing hospital readmissions.

Usage

This section provides detailed instructions on how to use the Heart Failure Prediction project.

Prerequisites

Before you begin, ensure you have:

  • Python 3.9 installed
  • Required libraries: Pandas, Numpy, Matplotlib, Seaborn, Plotly (Interactive Viz), Sci-Kit Learn.

Installation

To install this project, follow these steps:

git clone https://github.com/darshjoshi/heart_failure_prediction
cd heart_failure_prediction
pip install -r requirements.txt

About

CS 667: Practical Data Science - Final Project

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published