This is a simple web application detects probability of COVID-19 infection by analyzing symptoms of a person.
- General info
- Screenshots
- Technologies
- Setup
- Features
- Status
- Contact
- Authors and Contributers
- License
This application detects probability of COVID-19 infection in a person by analyzing symptoms.
COVID-19 tests are limited in daily basis thus everybody could not be tested in single day so this application could be very useful for medical authorities or medical professionals for prioritization of COVID-19 test cases.
Homepage
Result Page
THIS PROJECT IS BASED UPON SELF CREATED DATASET OF SYMPTOMS and LOGISTIC REGRESSION. This project can be enhanced by using dataset provided by medical authorities.
This application uses many external modules so before setting up this application in your local machine you need to install these softwares and modules.
Go to https://www.python.org/downloads/ , select OS and download the installer. Then run the installer, proceed further and finish the installation.
To install flask run your terminal with administrative priviliges and run following command.-
$ pip install flask
To start this application open terminal in application directory and run following command.-
$ python app.py
After this a URL will be displayed in terminal window, after typing that URL into browser window web apllication will start.
I could not figure out how to deploy this application in live environment. If anyone knows how to deploy this application in live server please help me with this issue. Credit will be given to you after successful deployment.
- Clean UI
- Useful for self assessment
- Very useful for Doctors and Medical authorities
To-do list:
- Live map with active and recovered cases.
- Many more improvements.
Project is: in progress
Created by Pushpendra Yadav Email - (pushpendray1337@gmail.com) Instagram - (https://instagram.com/sinister_1337) Feel free to contact me!
- Pushpendra Yadav - Initial work - COVID-19 Probability Detector
Anyone can help us by suggesting the new improvements and features.
I truly ❤️ pull requests! See also the list of contributors who participated in this project.