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Submission for the MedHacks2 Hackathon; An updated and improved version of one of my older projects from HS.

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TSKoduru/LANTERN

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LANTERN

An application to accurately detect Lyme disease!
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View Demo · Report Bug · Request Feature · Check out (Upvote?) the DEVPOST

Table of Contents
  1. About The Project

About The Project

Background

Back when I was a young kid, I got bitten by a tick and developed this large, bullseye-shaped rash. Here's what it looks like:


EM

Turns out, that was one of the damning symptoms of Lyme disease. Unfortunately, I wasn't able to get it diagnosed early enough, so I slowly lost control of my arms and legs over about a month. Eventually, I had to go to school in a wheelchair - It was bad.
Lyme actually has a pretty effective treatment; The problem is just in it's diagnosis. The rash that I got, though a pretty clear signal of Lyme, is often diagnosed as another type of disease. Here's an example of a rash that looks similar, but isn't Lyme:
EM

So, the goal was to develop a system that could accurately diagnose Lyme disease from a picture of a rash. This updated version of the system takes advantage of the newest in computer vision tech - transformers - To provide even more accurate results with even less data. I'm excited to see where this project goes, and I hope that it can help a lot of people.

Credit where credit is due: I worked with Edward Zhang, a friend of mine, on the first version of this project back in school. He was a huge help - Be sure to check out his insta here!

Some interesting statistics

Just so you know the extent of the problem, here are some statistics about Lyme disease:

As you can see, it's a pretty big issue.

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Built With

  • Python
  • Tensorflow
  • Keras
  • React.js
  • Flask
  • JavaScript

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Getting Started

Hey, thanks for checking out the project! You can check out a video demo of the project here, or see the DEVPOST here. Sorry that you can't run the project locally - I'm having issues trying to find a place to host it. If you have any suggestions, feel free to hit me up!

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License

Distributed under the GNU General Public License v3.0. See LICENSE for more information.

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Contact

Teja koduru - @TJKoduru - [email protected]

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About

Submission for the MedHacks2 Hackathon; An updated and improved version of one of my older projects from HS.

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