Heart Disease Prediction App

Welcome to the Heart Disease Prediction App repository! This application, built using Flask and powered by a Random Forest Classification model, aims to provide users with accurate predictions regarding the likelihood of heart disease based on various health parameters.

Dataset for the model is available here https://www.kaggle.com/datasets/johnsmith88/heart-disease-dataset

-> Entering data

-> When heart disease not found

-> When heart disease is found

Features

• Flask Web Application: The frontend is developed using Flask, ensuring a user-friendly and responsive interface.
• Random Forest Classification Model: The heart disease prediction model utilizes the Random Forest algorithm, offering high accuracy and robustness.
• User-friendly Interface: Easily input health parameters and receive predictions regarding the probability of heart disease.
• Interpretability: Gain insights into the factors influencing the prediction, enhancing user understanding.

Usage

1. Clone the Repository:

   git clone https://github.com/your-username/heart-disease-prediction-app.git
   cd heart-disease-prediction-app
   

2. Install Dependencies:

   pip install -r requirements.txt
   

3. Run the Application:

   python app.py
   

4. Access the App: Open your web browser and navigate to http://localhost:5000 to use the Heart Disease Prediction App.

Input Parameters

To make predictions, please provide the following health parameters:

To make predictions, please provide the following health parameters:

• Age: Enter your age.
• Sex (0 for female, 1 for male): Specify your gender (0 for female, 1 for male).
• Chest Pain Type (0-3): Indicate the type of chest pain experienced (0-3).
• Resting Blood Pressure: Input your resting blood pressure.
• Serum Cholesterol: Provide your serum cholesterol level.
• Fasting Blood Sugar: Enter your fasting blood sugar level.
• Resting Electrocardiographic Results: Specify resting electrocardiographic results.
• Maximum Heart Rate Achieved: Input the maximum heart rate achieved during exercise.
• Exercise Induced Angina (0 for no, 1 for yes): Indicate if you experience exercise-induced angina (0 for no, 1 for yes).
• ST Depression Induced by Exercise Relative to Rest: Enter the ST depression induced by exercise relative to rest.
• Slope of the Peak Exercise ST Segment: Specify the slope of the peak exercise ST segment.
• Number of Major Vessels Colored by Fluoroscopy (0-3): Indicate the number of major vessels colored by fluoroscopy (0-3).
• Thalassemia: Specify the type of thalassemia.

License

This project is licensed under the MIT License.

Thank you for using our Heart Disease Prediction App! Your feedback and contributions are highly appreciated.

Contributing

We welcome contributions! Feel free to explore the code, enhance the application, or address issues. Create a pull request or open an issue to start a discussion.