Covid-19 Patient/Non-Patient Risk Prediction using AI
Updated 29 Mar 2020

We have to planned a common Machine Learning tool for Reduce the Corona Spreading level based on their foods, medical history, social distance parameters.
The Risk Prediction patients based on their clinical check list. we have to plan a common tool for Prediction.
It's a common Tool GUI, The name itself , if you have local area patient checklist/attributes then easy to Train the Data using this GUI and finally predict the Risk level of Unknown Patients.
Train Data(Risk Level Known Patient) --> Feature Normalization --> optimized Feature Selection ---> Train The Classifier Test Data(Risk Level Unknown)--> Normalization---->selected Features---> Predict the Result with the help of Trained Classifier. In simple-ways, if you have your local area patient check list from that we have find the Risk prediction/Infection Chance. Most importantly , if we do in correct way, we will easy to find which are the parameters like foods and social distance type etc reduce the Covid-19 pandemic.

Cite As

Amburose Sekar (2024). Covid-19RiskPrediction (, GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2015b
Compatible with R2015b to R2020a
Platform Compatibility
Windows macOS Linux
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