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A tool for predicting Heart Disease probability based on ML model

Home Page: https://princeegy-heart-disease-prediction-app-fgg77d.streamlitapp.com/

License: MIT License

Jupyter Notebook 99.85% Python 0.15%
heartdisease heartdisease-prediction machine-learning python streamlit xgboost

heart-disease-prediction's Introduction

Heart Disease Prediction

Heart disease is the most common cause of death in the world, and approximately 1 in 5 people die from heart disease, this project can help predicting the probability of being affected by heart disease based on a well trained Machine Learning model

General Info

  • This project was created as a Mid-Project of Samsung Innovation Campus (SIC) training.
  • The application construct is located in the app.py file. This file uses dataset from Dataset folder and the pretrained model from Preprocessing & Modelling folder
  • XGBoost has got the best accuracy with 99% accuracy on predicting people with no HeartDisease and 91% accuracy on predicting people with Heart Disease

Team Members

Technologies

  • The app is fully written in Python 3.10.1, the user interface was created using streamlit 1.13.0
  • Libraries used: pandas, numpy, seaborn, matplotlib, sklearn, plotly, imblearn


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