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.

   

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

   

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.

   

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

   

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

   

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

Register Page

Dashboard

Disease Info Page

Value Input

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.

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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