CIRPMC: Critical Illness Risk Prediction Model for COVID-19
- R3.6
- caret
- e1071
- gbm
- randomForest
To clone the repository and install manually, run the following from a terminal:
git clone https://github.com/paprikachan/CIRPMC.git
cd CIRPMC
In command line:
Usage: predict_CIRPMC.R [options]
Options:
-i CHARACTER, --infile=CHARACTER
Path of X input file
-o CHARACTER, --outfile=CHARACTER
Path of Y output file
-h, --help
Show this help message and exit
The following code runs an example of CIRPMC.
predict_CIRPMC.R -i test_X.csv -o pred_Y.csv
Input file is a csv file, stores the measurements of 7 inflammatory markers for each patient:
- IL-1β (pg/mL, < 5.0)
- TNF-α (pg/mL, < 8.1)
- IL-6 (pg/mL, < 7.0)
- IL-10 (pg/mL, < 9.1)
- IL-8 (pg/mL, < 62)
- PCT (ng/mL, > 0)
- CRP (mg/L, > 0)
Note: CRP, C reactive protein. PCT, procalcitonin. TNF-α, tumor necrosis factor α. IL-1 β, interleukin 1β. IL-2R, IL-6, interleukin 6. IL-8, interleukin 8. IL-10, interleukin 10.
Out file is a csv file, stores the predicted results from CIRPMC:
- LR: The predicted critical illness probablity from logistic regression
- SVM: The predicted critical illness probablity from supported vector machine
- RF: The predicted critical illness probablity from random forest
- GBDT: The predicted critical illness probablity from gradient boosted decision tree
- NN: The predicted critical illness probablity from neural network
- Probability: The predicted critical illness probablity from our ensemble model CIRPMC
- Cluster: The predicted critical illness status, 0 or 1.
- Risk group: The stratified risk group, Non-critical or Critical.
If you have any questions or require assistance using CIRPMC, please open an issue.