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Website that implements the machine learning model for classifying the presence and correct placement of tubes on chest x-rays, allowing for easy access and practical application of the model by medical professionals.

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DAN3002/Doctors-Cyclop-Webapp

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Doctors Cyclop Webapp

Website that implements the machine learning model for classifying the presence and correct placement of tubes on chest x-rays, allowing for easy access and practical application of the model by medical professionals.

Doctor Cyclop is one project of the Phoenix team in FPT Edu Hackathon 2021. This repository contains code of the web interface for interact with the system. For the model, view Doctor-Cyclop-Hackathon-2021.

UI

Requirements

  • MeteorJS 2.1
  • NodeJS 12
  • MongoDB 4.2
  • AWS S3

Config

  • Create file .env and copy content from .env_dummy. Fill in all information needed.
  • You can change MONGO_URL or ROOT_URL in file run.sh

Run

  • Install packages
npm install
  • Run file run.sh then open http://localhost:3000 in your browser to access web app.
./run.sh

Setup model server

Run model server from this repository. Then copy the url of model server to Model Url in setting page.

Copyright and License

The template was developed based on SB Admin 2.

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Website that implements the machine learning model for classifying the presence and correct placement of tubes on chest x-rays, allowing for easy access and practical application of the model by medical professionals.

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