CIRPMC: Critical Illness Risk Prediction Model for COVID-19

Pre-requirements

R3.6
caret
e1071
gbm
randomForest

Installation

Installation from Github

To clone the repository and install manually, run the following from a terminal:

git clone https://github.com/paprikachan/CIRPMC.git
cd CIRPMC

Usage

Help page

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

Quick start

The following code runs an example of CIRPMC.

predict_CIRPMC.R -i test_X.csv -o pred_Y.csv

File format

Input file

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.

Output file

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.

Cite us

Help

If you have any questions or require assistance using CIRPMC, please open an issue.

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CIRPMC (Critical Illness Risk Prediction Model for COVID-19)

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