SymptoCure 🩺💻

Project Overview

SymptoCure is a comprehensive healthcare platform that combines machine learning-powered disease detection with remote doctor consultation, providing users with an end-to-end health management solution.

🌟 Key Features

• Intelligent Symptom Analysis

  • ML-powered disease prediction
  • Comprehensive symptom input system
  • Accurate medical diagnostics

• Doctor Consultation

  • Specialist doctor matching
  • Easy appointment booking
  • Seamless communication platform

• User Management

  • Secure authentication (JWT)
  • Separate patient and doctor dashboards
  • Profile management

🛠 Technologies Used

Frontend

• React.js
• React Router
• Tailwind CSS
• Axios

Backend

• Node.js
• Express.js
• MongoDB
• FastAPI (Python)

Machine Learning

• Python
• Scikit-learn
• Kaggle Datasets
• Machine Learning Prediction Models

Additional Technologies

• JWT Authentication
• Socket.IO (Real-time communication)

🚀 Getting Started

Prerequisites

• Node.js (v14+)
• Python (v3.8+)
• MongoDB
• pip

Installation Steps

1. Clone the repository

git clone https://github.com/harshp4114/SymptoCure.git
cd symptocure

2. Install Backend Dependencies

# Main Backend
cd backend
npm install

# ML Backend
cd ml-backend
pip install -r requirements.txt

3. Install Frontend Dependencies

cd frontend
npm install

4. Run the Application

# Start Backend
cd backend
npm start

# Start ML Backend
cd ml-backend
uvicorn main:app --reload

# Start Frontend
cd frontend
npm start

🤖 Machine Learning Model

The disease prediction model is trained on curated medical datasets from Kaggle, utilizing various machine learning algorithms to provide accurate predictions based on user-input symptoms.

🔐 Authentication Flow

1. User Registration (Patient/Doctor)
2. JWT Token Generation
3. Secure Route Protection

🙏 Acknowledgements

• Kaggle Datasets
• Open-source libraries