martinakaduc/BeCaked
This is the implementation for our paper about an explainable artificial model for COVID-19 forecasting.
This project offers an explainable AI model for forecasting COVID-19 trends. It takes historical COVID-19 data as input and provides future case predictions along with explanations for those forecasts, viewable as plots. Public health officials, epidemiologists, and researchers can use this to understand and anticipate disease progression at global or country levels.
No commits in the last 6 months.
Use this if you need to forecast COVID-19 trends and also understand the underlying factors driving those predictions.
Not ideal if you require real-time, highly granular local outbreak predictions, or if you are not comfortable running command-line scripts.
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Language
HTML
License
GPL-3.0
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Last pushed
Jun 29, 2024
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