The objective of this project is to detect whether the person has any chances of heart disease or not by giving number of features to patients with having maximum accuracy of above 97%. By Using Machine learning algorithms and deep learning are applied to compare the results and analysis of the UCI Machine Learning Heart Disease dataset.
👉 https://med-x-webapp.herokuapp.com/
| Sr no | Algorithm Used | Accuracy |
|---|---|---|
| 1 | K - Nearest Neighbor | 97.82% |
| 2 | Random Forest | 86.95 % |
| 3 | Ada Boost With Random Forest | 93.47 % |
| 4 | Gradient Boosting | 89.91% |
Home Page
Form Details
Prediction Result- Person with Heart Disease
Prediction Result- Person Who don't have Heart Disease
-Fork the repository
- Clone or download the repo.
- Open command prompt in the downloaded folder.
- Create a virtual environment.
virtualenv environment_name
- Activate the New Environment
source environment_name/bin/activate
- Install the Dependencies.
pip install -r requirements.txt
- Run the Flask App.
python app.py
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