Inspiration
It would help a lot if the average person is able to get an indication of their chance of already being infected. This would help them to make the choice of coming out of isolation and taking the risk of going out and getting consulted
What it does
This portable ML code uses Decision Tree algorithm to learn from an existing large COVID dataset, the dependence of the chance of being infected, on 8 fundamental factors.
Accomplishments that we're proud of
This code is a very simple implementation that involves minimum processing overhead and yet is able to indicate the possibility of a being infected with an accuracy of 85%, using just 8 simple questions.
What's next for COVID Detection using portable ML
Next in line is to embed the code into a mobile application so that it is easily available for the average person.
Log in or sign up for Devpost to join the conversation.