https://github.com/josephmars/covid19_death_prediction

Shiny app to predict the risk of death by COVID-19 based on demographic data. Support Vector Machine (SVM) and XGBoost were used.
https://github.com/josephmars/covid19_death_prediction

epidemiology healthcare-ai machine-learning

Last synced: 5 months ago
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Shiny app to predict the risk of death by COVID-19 based on demographic data. Support Vector Machine (SVM) and XGBoost were used.

• Host: GitHub
• URL: https://github.com/josephmars/covid19_death_prediction
• Owner: josephmars
• Created: 2024-06-18T21:40:06.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2025-01-26T11:37:30.000Z (9 months ago)
• Last Synced: 2025-02-16T19:45:59.732Z (8 months ago)
• Topics: epidemiology, healthcare-ai, machine-learning
• Language: R
• Homepage:
• Size: 1.53 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Prediction of risk of death by COVID19 (2020)

Shiny app to predict the risk of death by COVID-19 based on demographic data. It leverages the classification model SVM trained on public available data from the Colombian Ministry of Health. The app is in Spanish.

![App diagram](docs/images/diagram.png)

Demographic data:

- Age

- Sex

- City and department

- Days before notification of symptoms

How to run the app:

1. Clone the repository

2. You can run the app by running `shiny::runApp("app")` in R.

## Acknowledgments

- Data provided by the Colombian Ministry of Health.

- Model trained togethr with the Analytics Research Lab of the Universidad del Norte.