AI-HealthCare-Assistant

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🚀 2026 Update: Project Evolution Notice

Important Notice: This repository contains the original 2022 academic prototype of the NearestDoctor Healthcare platform.

Thank you to everyone who supported this project with stars, forks, and feedback. The V1 codebase (React/Express/Node) available here remains open-source under the Apache 2.0 license for educational purposes.

However, the project’s vision has been taken forward exclusively by Ahlem Laajili and evolved into a proprietary, commercial startup.

The entire platform has been rewritten from scratch by Ahlem Laajili using a modern tech stack (Next.js, FastAPI, advanced LLMs, and cloud-native infrastructure). It is now closed-source to protect the new Intellectual Property (IP) owned solely by her. The V2 code (including the FastAPI and Next.js upgrades) will not be pushed to this repository.

If you are interested in the future of NearestDoctor, enterprise solutions, or participating in our upcoming beta, please reach out to Ahlem Laajili directly or stay tuned!

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📖 Table of Contents

• About The Project
• Key Features
• Tech Stack
• Architecture
• Getting Started
• How It Works
• Screenshots
• Roadmap
• Achievements
• Contributing
• Team
• Acknowledgments

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🧠 About The Project

NearestDoctor is a full-stack, AI-powered healthcare web application that bridges the gap between patients and medical professionals. It combines machine learning, blockchain, facial recognition, and natural language processing into a seamless platform that covers the entire patient journey from first symptom to secured medical record.

💡 “Every patient deserves professional medical guidance, instantly and securely — no matter where they are.”

The Problem

Despite advances in digital health, patients still face three core challenges:

• 🔍 Finding the right doctor: it’s hard to know which specialist fits your symptoms.
• 📆 Getting an appointment: scheduling is manual, slow, and rarely location-aware.
• 🔐 Securing medical records: records are fragmented, inaccessible, and vulnerable to breaches.

NearestDoctor was designed from the ground up to solve all three.

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✨ Key Features

Feature	Description
🤖 AI Symptom Detection & Chatbot	Patients chat with a Dialogflow-powered bot, describe symptoms, and receive an illness prediction with the right specialist recommendation.
📍 Location-Based Doctor Search	Find the nearest doctor or first available appointment in real time.
📅 Smart Appointment Scheduling	Book with the nearest doctor or earliest available slot directly through the chatbot flow.
🔗 Blockchain Medical Records	Patient data is stored on Ethereum using smart contracts. Every update creates a verifiable, immutable transaction block.
🫁 X-Ray Lung Diagnosis	Doctors upload chest X-rays; a TensorFlow pre-trained model predicts COVID-19, tuberculosis, or pneumonia in seconds.
🧠 Mental Health Test	Patients take a guided quiz to assess their mental wellbeing, then receive a result and curated article suggestions.
🪪 Doctor Identity Verification	Doctors verify their real identity using a national card ID processed through the Nanonets AI OCR API before they can register.
🤳 Multi-Mode Authentication	Three login options: LinkedIn OAuth, username/password, or Face ID (TensorFlow deep learning model).
📰 Blogs & Web Scraping Search	Doctors publish articles; an integrated web scraping engine lets users search for external medical content by keyword.
🛒 Paramedical E-Shop	ML-based patient behavioral analysis drives personalized product recommendations.
🎙️ AI Voice Assistant	ALAN SDK integration lets users navigate the platform entirely by voice commands.
💳 Integrated Payments	Stripe API handles doctor subscription plans and patient service payments.

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🚀 Tech Stack

Layer	Technology	Version
Frontend	React.js	v18
Backend API	Node.js + Express.js	Node v16.13.1 / Express v4.17.1
AI/ML Microservices	Python + Flask	Flask v2.1
Database	MongoDB	v5.9.1
Blockchain	Ethereum Smart Contracts	—
Face Recognition	TensorFlow (pre-trained deep learning model)	—
ID Card OCR	Nanonets AI API	—
Chatbot (Symptoms + Appointments)	Dialogflow	—
X-Ray Diagnosis	TensorFlow (pre-trained model)	—
Maps & Location	Google Maps API	—
Voice Assistant	ALAN SDK	—
Payments	Stripe API	—
OAuth	LinkedIn OAuth	—
Languages	JavaScript, Python, HTML5, CSS	—

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📐 Architecture

The platform follows a microservices-inspired MERN architecture:

• The React.js frontend communicates with the Node/Express REST API for core operations.
• AI features run as independent Flask microservices (symptom detection, face recognition, X-ray diagnosis, OCR, behavioral analysis).
• MongoDB stores application data users, appointments, blogs, shop inventory.
• Ethereum smart contracts handle patient medical records with immutability and permission-based access control.

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✅ Getting Started

Prerequisites

• Node.js v16+ and npm or yarn
• MongoDB running locally or via a cloud URI (v5.9.1+)
• Python 3.8+ for AI/ML microservices
• Git

Installation

1. Clone the repository

   git clone https://github.com/ahlem-phantom/AI-HealthCare-Assistant.git
   cd AI-HealthCare-Assistant
   

2. Install Node.js dependencies

   npm install
   # or
   yarn install
   

3. Install Python dependencies (for AI services)

   pip install -r requirements.txt
   

4. Configure environment variables

   Create a .env file in the root directory:

   MONGO_URI=your_mongodb_connection_string
   JWT_SECRET=your_jwt_secret
   PORT=5000
   STRIPE_SECRET_KEY=your_stripe_key
   GOOGLE_MAPS_API_KEY=your_maps_key
   DIALOGFLOW_PROJECT_ID=your_dialogflow_project_id
   NANONETS_API_KEY=your_nanonets_key
   

5. Start the main development server

   npm run development
   

6. Start Flask AI microservices (in a separate terminal)

   cd py-side
   flask run
   

7. Open the app at http://localhost:3000 🎉

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🔄 How It Works

For Patients

1. Select Role — choose “Patient” at the landing screen.
2. Register & Log In — via username/password or LinkedIn OAuth.
3. Describe Symptoms — chat with the Dialogflow AI bot; receive a specialist recommendation.
4. Mental Health Check — take the guided quiz and get personalized article suggestions.
5. Book an Appointment — schedule with the nearest or first-available doctor via the chatbot and Google Maps.
6. Medical Records — your records are securely stored on the blockchain; grant selective access to your chosen doctors.

For Doctors

1. Verify Identity — upload your national card ID; Nanonets OCR confirms authenticity in real time.
2. Register Face ID — enroll your face using the TensorFlow model for future biometric logins.
3. Choose a Plan & Pay — select a subscription tier and complete payment via Stripe.
4. Log In — use LinkedIn OAuth, username/password, or a live Face ID camera scan.
5. Use the Dashboard — manage appointments, write blogs, run X-ray lung diagnoses (COVID / TB / pneumonia), and access patient records via blockchain with granted permission.

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📸 Screenshots

1. Choose a Role	2. Face ID Login
3. Card ID Verification	4. Verification Success
5. Blog & Forum	6. Web Scraping Search
7. Appointments List	8. Symptom Selection
9. AI Specialist Suggestions	10. Chatbot Recommendations

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🗺️ Roadmap

• Phase 1 — Study & Prototyping

  • Problem definition, state of the art & competitive analysis
  • Feasibility study, wireframes

• Phase 2 — Design & Initial Build

  • Data model & physical/logical architecture design
  • Static frontend + first Node.js components

• Phase 3.1 — Feature Implementation (V1)

  • Full backend REST API
  • Frontend integration with all services
  • Core AI modules: symptom detection, face ID, OCR verification

• Phase 3.2 — Finalization & Deployment (V1.5)

  • X-ray diagnosis, mental health test, blockchain records
  • Final integration, system testing & deployment

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🏆 Achievements

🎖️ NearestDoctor was selected among dozens of projects to participate in the 9th Edition Ceremony of Best Engineering Projects of 2022 at Esprit School of Engineering, Tunisia.

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🤝 Contributing

Contributions are welcome! Here’s how to get started:

1. Fork the project
2. Create your feature branch

   git checkout -b feature/AmazingFeature
   

3. Commit your changes

   git commit -m "Add AmazingFeature"
   

4. Push to the branch

   git push origin feature/AmazingFeature
   

5. Open a Pull Request

See open issues for ideas and known bugs. Don’t forget to ⭐ star the project if you find it useful!

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👥 Team

Built with 💕 by AlphaCoders 5 engineering students from Esprit School of Engineering, Tunisia.

Project Mentor: [email protected]

Ahlem Laajili	Skander Turki	Syrine Zahras	Hichem Ben Zammal	Nesrine Ben Mahmoud

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⚠️ Deprecation Notice

Important: This project prototype was built in 2022 and several of its core libraries and dependencies are now outdated or deprecated. The codebase across react-app/, server/, py side/, and blockchain/ may require dependency updates or patches before it can be safely run in a modern environment.

Known areas built with legacy 2022 configurations:

• React: Uses older setups without Vite.
• Node.js / Express: Some deprecated dependencies; npm audit is recommended.
• Python / Flask: AI service modules need careful version-pinning.

While we do not officially support updates to this legacy public V1 anymore (as development has moved to the V2 startup), educational forks are welcome to tweak and learn from the code!

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🙌 Acknowledgments

• Choose an Open Source License
• GitHub Pages
• Img Shields
• Font Awesome
• Devicons

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