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MediQueue

A comprehensive healthcare queue and management platform designed to streamline patient, doctor, and admin interactions. Built with a modern tech stack for real-world healthcare needs.


Table of Contents


Project Overview

MediQueue is a full-stack web application that digitizes and optimizes healthcare queue management. It enables patients to book appointments, doctors to manage schedules, and admins to oversee operations, all in a secure and user-friendly environment.

Features

  • User authentication (patients, doctors)
  • Appointment booking and management
  • Doctor and patient dashboards
  • Family health management
  • Teleconsultancy support
  • Health metrics tracking
  • Lab report uploads
  • Insurance marketplace
  • Emergency services
  • Health content/blogs
  • Admin controls and analytics

Tech Stack

Frontend:

  • React (Vite)
  • Tailwind CSS
  • Axios

Backend:

  • Node.js
  • Express.js
  • MongoDB (Mongoose)
  • Cloudinary (media uploads)
  • Nodemailer (email service)

Other:

  • JWT Authentication
  • Multer (file uploads)
  • Swagger (API docs)

Architecture

frontend/   # React app (Vite, Tailwind)
backend/    # Node.js/Express API
  ├── config/
  ├── controllers/
  ├── middlewares/
  ├── models/
  ├── routes/
  └── utils/

Setup & Installation

Prerequisites

  • Node.js (v18+ recommended)
  • MongoDB (local or Atlas)

Backend

cd backend
npm install
# Configure .env (see .env.example)
npm run dev

Frontend

cd frontend
npm install
npm run dev

Usage

  • Visit the frontend URL (default: http://localhost:5173)
  • Register/login as a Patient, Doctor
  • Explore dashboards, book appointments, manage health data

API Endpoints

  • RESTful endpoints for users, doctors, appointments, health data, etc.
  • See backend/routes/ and Swagger docs for details

Contributing

  1. Fork the repo
  2. Create a feature branch
  3. Commit changes with clear messages
  4. Open a pull request

License

MIT License


Contact

Name: Neeraj Kaushik
Email: Neerajkaushik.1007@gmail.com
LinkedIn: www.linkedin.com/in/neeraj-kaushik1007
GitHub: https://github.com/Neerajkaushik07


Login Credentials (For Testing)

All generated profiles follow the requested format for testing.

Doctors

Patients

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