vqrca/bootcamp_alura_projeto_final

Machine Learning na Saúde: Prevendo a Necessidade de Internação em Leitos de UTI Durante a Pandemia de COVID-19

21
/ 100
Experimental

This project helps hospital administrators and healthcare providers predict which COVID-19 patients are likely to need an Intensive Care Unit (ICU) bed. By analyzing patient data, including demographics, pre-existing conditions, lab results, and vital signs collected within the first two hours of admission, the system outputs a prediction of whether a patient will require ICU admission. This allows for better resource planning and patient flow management.

No commits in the last 6 months.

Use this if you need to quickly assess the likelihood of COVID-19 patients requiring ICU care to optimize hospital bed allocation and operational efficiency.

Not ideal if you need predictions for diseases other than COVID-19 or require real-time updates beyond the initial two-hour admission window.

hospital-administration healthcare-operations patient-triage resource-planning pandemic-management
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 0 / 25

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11

Forks

Language

Jupyter Notebook

License

MIT

Last pushed

Aug 08, 2021

Commits (30d)

0

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