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The CAD Model for DiaScan.
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Processed Images after using the Graham Lighting Method
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Proof of 94+% accuracy of model
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Plotted Split of Test and Train data using Matlab
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graphed split of data based on severity of Diabetic Retinopathy.
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Frist Processing of Retina Scans.
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Processed Image of eye plotted using Matlab to for training the model.
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Original Images of Retina's
EyeSnap: Diabetic Retinopathy Detection with DiaScan - HackHarvardFall2023
Introduction
Welcome to the future of healthcare, where your smartphone becomes your guardian for early diabetes detection. Our innovative solution harnesses the power of artificial intelligence to identify Diabetic Retinopathy right from the convenience of your smartphone. We are on a mission to make early diabetes diagnosis accessible and effortless for everyone.
Diabetic Retinopathy
About Diabetic Retinopathy Diabetic retinopathy is a serious eye condition that affects individuals with diabetes. It can lead to vision problems and even blindness if left untreated. This single-page website aims to provide a clear and concise explanation of diabetic retinopathy.
Key Components
#### Retinal AI Retinal AI is the CNN Trained Model that can detect the presence and severity of Diabetic Retinopathy. It forms the heart of our solution, providing accurate and reliable results.
#### DiaScan DiaScan is a revolutionary 3D printed device that helps us scan the retina using a phone camera. The DiaScan fits around the phone like a case and allows us to take retinal scan photographs, enabling easy and non-invasive detection of diabetic retinopathy.
About Us
Author : Kartikey Pandey
As driven Computer Science student located in Pennsylvania with a strong interest in AI and Full Stack development, I've made notable contributions within the Intel AI4Youth program.As both an apprentice and intern, I've been selected for my dedication, and I've played a crucial role in creating impactful solutions to tackle issues that a global scale. With this new solution I have focused in increase Health Equity and detect diabetes using Retinal Scans in patients.
I believe in the power of early detection and its potential to transform healthcare. Join me in this journey towards a world where everyone can have easy access to early diabetes diagnosis and treatment.
Story behind this Project
I got the inspiration of this project from CareYaya was able to deeply connect with the issue as my own grandfather passed away three years ago due to Kidney Failure which was caused due to Diabetes Type 2. Listening to Neal K. Shah I was deeply moved and wanted to build a solution to this problem.
Contact Us
Email: Kartikeypandey.official@gmail.com
You can connect with me on Linkedin or mail me to further understand SnapEye.
Together, we can make a difference in the fight against diabetic retinopathy. Your smartphone is now your guardian in the battle for early detection and prevention.
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