quickD

DETECTING DIABETIC RETINOPATHY USING COMPUTER VISION
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Table of Contents

• Table of Contents
• About The Project
  • Built With
• Getting Started
  • Installation
• Usage
• Contributing
• License
• Contact
• Acknowledgements

About The Project

The diagnosis of DR currently using typical retinal fundus photography requires and depends on a skilled reader for the manual DR assessment opens to the inconsistency of the diagnosis. We aim to improve the diagnosis process for Diabetic Retinopathy patients using Computer Vision. Screening through mobile made queuing for doctor to do DR eye screening no more necessary. Moreover, our model give a result up to 97% accuracy.

Built With

• Python
• Javascript
• Flask
• React Native
• Google Cloud Platform

Getting Started

To use the app for diagnosis, please follow these simple steps.

Installation

Install the mobile app by downloading the apk file in apk\app-release.apk

Usage

Contributing

Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.

License

Distributed under the MIT License. See LICENSE for more information.

Contact

• Muhammad Laziem - muhdlaziem@gmail.com
• Aishah Nabilah - ainachmrj@gmail.com
• Puteri Ameena - puteriameena.iium@gmail.com
• Muhammad Amiruddin - m.amiruddin27@gmail.com

Project Link: https://github.com/muhdlaziem/DR

Acknowledgements

• Assoc. Prof. Dr. Amelia Ritahani, Project Supervisor, Kuliyyah of Information Communication Technology IIUM Gombak Campus - amelia@iium.edu.my
• Mrs. Nurul Ain Binti Yahaya, Optometry Lecturer, Kuliyyah of Allied Health Science Kuantan IIUM Kuantan Campus - nurulainyahaya@iium.edu.my
• Mr. Selvah Karthikesu, Mentor, Roche - selvah.karthikesu@roche.com