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Health Companion

Welcome to the Health Companion repository! This project aims to provide a comprehensive health monitoring and prediction tool using machine learning. The application can predict the risk of various diseases such as stroke, cardiovascular diseases, and diabetes. It also includes a BMI calculator and a calorie calculator.

GitHub Repository: Health Companion

Table of Contents

  1. Introduction
  2. Features
  3. Technologies Used
  4. Installation
  5. Usage
  6. Database Schema
  7. Screenshots
  8. Future Enhancements
  9. Contributing
  10. License

Introduction

Health Companion is a web application designed to help users monitor and predict their risk for certain health conditions using machine learning algorithms. The application is user-friendly and provides detailed information and insights based on user input.

Features

  • Disease Prediction: Predicts the risk of stroke, cardiovascular diseases, and diabetes.
  • BMI Calculator: Calculates Body Mass Index (BMI) based on height and weight.
  • Calorie Calculator: Estimates daily calorie needs based on various factors.
  • User Authentication: Secure login and registration for personalized experience.

Technologies Used

  • Frontend: HTML, CSS, JavaScript
  • Backend: Python (Flask)
  • Database: MySQL
  • Machine Learning: Various ML models for disease prediction

Installation

  1. Clone the repository:

    git clone https://github.com/Rakshitgupta9/Health-Companion.git

  2. Navigate to the project directory:

    cd Health-Companion

  3. Install the required packages:

    pip install -r requirements.txt

  4. Set up the database:

    • Import the SQL files located in the database folder into your MySQL database.
    • Update the database connection details in the app.py file.

  5. Run the application:

    python app.py

Usage

  1. Login: Access the application by logging in with your credentials. If you don't have an account, you can register a new one.

    Login Page

  2. Register: Create a new account by providing the necessary information.

    Register Page

  3. Dashboard: Once logged in, you can navigate to various features such as stroke risk prediction, cardiovascular disease prediction, diabetes risk prediction, BMI calculator, and calorie calculator.

    Dashboard

  4. Disease Prediction: Enter the required information to get a prediction for the risk of stroke, cardiovascular disease, or diabetes.

    Disease Info Page

  5. Results: View the prediction results along with additional insights and suggestions.

    Value Input Result Page Result Page

Database Schema

account_cardiovascular

Column Type Description
id INT Primary Key
age1 INT Age
gender1 INT Gender
height FLOAT Height
weight FLOAT Weight
ap_hi INT Systolic Blood Pressure
ap_lo INT Diastolic Blood Pressure
cholesterol INT Cholesterol Level
glu INT Glucose Level
smoke INT Smoking Status
alco INT Alcohol Intake
active INT Physical Activity
CARDIO_DISEASE INT Cardiovascular Disease Risk

account_dia

Column Type Description
id INT Primary Key
pregnancies INT Number of Pregnancies
glucose INT Glucose Level
bloodpressure INT Blood Pressure
skinthickness INT Skin Thickness
insulin INT Insulin Level
bmi_dia FLOAT BMI
diabetes_pedigree_fnc FLOAT Diabetes Pedigree Function
age_dia INT Age
outcome INT Diabetes Risk

accounts

Column Type Description
id INT Primary Key
username VARCHAR(50) Username
password VARCHAR(255) Password
email VARCHAR(100) Email

account_stroke

Column Type Description
id INT Primary Key
gender INT Gender
age INT Age
hypertension INT Hypertension Status
heart_disease INT Heart Disease Status
ever_married INT Marital Status
work_type INT Type of Work
residence_type INT Type of Residence
avg_glucose_level FLOAT Average Glucose Level
bmi FLOAT BMI
smoking_status INT Smoking Status
stroke INT Stroke Risk

Screenshots

Login Page

Login Page

Register Page

Register Page

Dashboard

Dashboard

Disease Info Page

Disease Info Page

Value Input

Value Input

Result Page

Result Page Result Page

Future Enhancements

  • Doctor Information: Provide information about doctors near the user's location for specific diseases.
  • Remedies and Tips: Offer remedies and health tips based on the user's health data.
  • More Disease Predictions: Expand the application to predict risks for additional diseases.

Contributing

Contributions are welcome!

License

This project is licensed under the MIT License. See the LICENSE file for details.

Thank you for visiting the Health Companion repository! If you have any questions or feedback, feel free to open an issue or contact us.

GitHub: Rakshitgupta9