ahlem-phantom / AI-HealthCare-Assistant

AI Healthcare Assistant that provides medical services to patients and doctors using chatbots to interact with them. It uses blockchain for storing medical reports and machine learning algorithms for illness detection and patient satisfaction prediction.

💕 AI-HealthCare-Assistant

AI-HealthCare-Assistant

This is the official AI-HealthCare-Assistant documentation

Table of Contents

1. About The Project
   • Project Main Features
   • Project Technical Architecture
   • Built With
2. Getting Started
   • Prerequisites
   • Installation
3. Usage
4. Roadmap
5. Achievements
6. Contributing
7. Contact
8. Acknowledgments

📃 About The Project

"NearestDoctor" is an AI healthcare assistant that uses AI and machine learning algorithms to improve patients' experience by providing them professional medical assistance. Patients will be able to find the nearest doctor to their location, ask about illness symptoms, and schedule an appointment with a doctor based on their availability. Immediate responses will be provided by a chatbot to redeem the needs of our patients using Artificial Intelligence techniques for decision making. Also, our solution offers a very unique concept with developing patient records using Blockchain. The assistant will create a medical record and store it in Blockchain to make them accessible to any of the patient's chosen doctors with granted permission. Thanks to the decentralized nature of Blockchain, patient records would be securely spread among a large number of servers, posing little risk to their sensitive information.
This web application centralizes the schedules and medical services in a single dashboard. This solution offers a real-time overview of the coverage of reports that facilitate the management of resources.

📜 Project Main features

1. 🤖 Symptoms Detection: using Artificial Intelligence for specialist recommendation and illness detection.
2. 📅 Appointment Scheduling: based on the nearest doctor to your location or the first available appointment.
3. 📘 Medical Records: securely stored in the blockchain using smart contracts.
4. 💬 Blogs and Forum: using machine learning for patient satisfaction prediction.
5. 📈 Real-time reports: using machine learning to offer an overview of many aspects of the application.
6. 🙋 Advanced authentication: using facial recognition to match the identity of a doctor, Card ID data extraction, and machine learning for identity verification.
7. 🛒 Paramedical e-shop: using machine learning for patient's behavioral analysis prediction.

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📐 Project Technical Architecture

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🚀 Built With

NearestDoctor is built using MERN Stack technology. You may find below the list of the frameworks/libraries that we used to build our project :

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✨ Getting Started

To get a local copy up and running follow these simple example steps.

🚧 Prerequisites

You may find below the list of things you need to use this project :

• Make sure MongoDB is running on your system.
• You will need to install the "yarn" or "npm" command line.

🛠 Installation

In order to install the app you need to follow the instructions below :

1. Clone the repo

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

2. Install NPM packages dependencies

   npm install 

   Or

   yarn install 

3. Run the server on

   npm run development

4. Open localhost:3000 in the browser and that's it you can enjoy the project 🎉!

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⚡ Usage

Use this space to show useful examples of how a project can be used. Additional screenshots, code examples and demos work well in this space. You may also link to more resources.

Choose a role	FaceID Login
CardId verification	Success of cardID verification
List of blogs	Web scraping search
List of appointements	Symptoms detection : List of symptoms
Symptoms detection : Suggestions	Symptoms detection : Suggestions

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🚩 Roadmap

See the open issues for a list of proposed features (and known issues).

• Phase 1 : Project Study, Requirement Analysis and Prototyping

  • Problematic definition
  • State of the art
  • Preliminary Feasibility Study
  • Solution & functional/technical requirements
  • Wireframes of the solution

• Phase 2 : Advanced Features Specification, Application Design & Realization

  • Data Model
  • Physical architecture and technical environments
  • Specification of the advanced features
  • Advanced Feasibility Study (Cases studied problems and Results - development Back-end)
  • Development of static user interfaces (Front-end)-> depending on the project
  • First NodeJS components (scenarios and case studies tests)
  • Static User Interfaces (Front-end)

• Phase 3.1 : Realization Of Advanced Features, Deployment And Tests

  • Implementation of the solution (V1)
  • Continuation Back-End development
  • Collecting and using flow from external application(Phase 2 + Phase 3)
  • Consuming REST services by the front-end
  • Development of final user interfaces (Front-end)
  • Exposing REST services by the back-end Node.js
  • Integration
  • Implemented Application V1

• Phase 3.2 : Realization Of Advanced Features, Deployment And Tests

  • Finalization of final delivrable (V2)
  • Final Integration/Deployment of the solution
  • Tests
  • Implemented Application V2
  • Tests results

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🏆 Achievements

So far, NearestDoctor has been selected among dozens of projects to participate in the 9th edition ceremony of best projects of the year 2022 in Esprit school of engineering.

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😎 Contributing

If you have a suggestion that would make this project better, please fork the repo and create a pull request. Any contributions you make are greatly appreciated. Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (git checkout -b Yourbranch)
3. Commit your Changes (git commit -m 'Add some features to project')
4. Push to the Branch (git push origin Yourbranch)
5. Open a Pull Request

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💌 Contact

Project Mentor : [e-mail]

Project Members :

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

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🙌 Acknowledgments

• Choose an Open Source License
• GitHub Emoji Cheat Sheet
• Img Shields
• GitHub Pages
• Font Awesome

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Developed with 💕 by AlphaCoders.