How can the US government and hospitals better manage and prepare their resources and healthcare personnel? Covid-19 has stressed hospitals and healthcare workers. We want to tackle this problem with Machine Learning that would predict how many inpatients beds are used and available in a typical week grouped by State and the City.
- if we can understand which hospitals/other categories are most stressed with work and predict with ML, we can improve the quality of healthcare by distributing the work.
The prompt for the Datathon can be found here:
https://share-docs.clickup.com/26455927/d/h/t7bvq-348/40c04786de66f7b/t7bvq-1768
Our .csv file was modified and given to us by the datathon organizers. The original source comes from here:
https://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/anag-cw7u
- In your preferred IDE make sure python has been setup (we recommend VS Code)
- Jupyter notebook and all its basic requirements should be setup
- The 'COVID-19_Reported_Patient_Impact_and_Hospital_Capacity_by_Facility.csv' should be download and placed in your IDE's folder
- Before running make sure the following libraries have already been downloaded:
- Pandas
- Sklearn
- Numpy
- Matplotlib
- Seaborn
- Plotnine
- Os
We won 1st in the Health Track and 2nd for our outstanding Machine Learning Model.