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

• Ahmed Mohsen
• Hossam Galal
• Yomna Ramdan

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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