https://github.com/xtremilicious/covid-19-probability-detection

Analyzes data for probable symptoms of COVID-19 and suggests the probability of being affected by it. This will help in prioritizing the actual checkup for the patients having higher probability.
https://github.com/xtremilicious/covid-19-probability-detection

coronavirus covid-19 machine-learning python3

Last synced: 25 days ago
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Analyzes data for probable symptoms of COVID-19 and suggests the probability of being affected by it. This will help in prioritizing the actual checkup for the patients having higher probability.

• Host: GitHub
• URL: https://github.com/xtremilicious/covid-19-probability-detection
• Owner: Xtremilicious
• Created: 2020-04-11T14:39:18.000Z (almost 5 years ago)
• Default Branch: master
• Last Pushed: 2020-04-11T15:01:42.000Z (almost 5 years ago)
• Last Synced: 2024-10-19T03:05:36.544Z (3 months ago)
• Topics: coronavirus, covid-19, machine-learning, python3
• Language: Jupyter Notebook
• Homepage:
• Size: 28.3 KB
• Stars: 2
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        

# COVID-19 Probability Detection

## Abstract

The cases for the patients affected by COVID-19 or Coronavirus is increasing at an exponential rate. This leads to an increase in the patients who have visible symptoms who need to be tested for the virus. The idea is to find out the probability/chance of a patient being affected by the the virus by comparing and analyzing the symptoms from the previous confirmed cases of virus-affected patients.

The patients who have a higher probability can be prioritized to have a checkup before the patients who have a lower probability. This measure will help detect positive cases in patients much faster than selecting and testing random patients.

## Dataset

The dataset used in this project is **randomly generated** and hence the predictions are **not accurate**. Using an actual dataset with real data involving affected patients will generate much better results.

##  Run it!

Install the required dependencies

    pip install pandas numpy sklearn tensorflow flask pickle

Run the code:

    python myTraining.py

    python main.py