For the most part, I used the documentation of the following libraries:
Articles and posts that helped this project:
- COVID-19 - Clinical Data to assess diagnosis (Kaggle)
- Tour of Evaluation Metrics for Classification
- ICU outcomes and survival in patients with severe COVID-19
- Venous blood gas analysis in patients with COVID-19 symptoms
- Blood routine test in mild and common 2019 coronavirus (COVID-19) patients
- Predicting the Need for ICU Admission in COVID-19 Patients Using XGBoost
- Using machine learning tools to predict outcomes for emergency department intensive care unit patients
- Comparing machine learning algorithms for predicting ICU admission and mortality in COVID-19
- Machine Learning Approach to Predicting COVID-19 Disease Severity
- Useful Metrics to Evaluate Binary Classification Models
- Metrics to Evaluate your Machine Learning Algorithm
- How to Use ROC Curves and Precision-Recall Curves for Classification in Python