StableCox
Nature machine intelligence-Stable Cox Regression for Survival Analysis under Distribution Shifts
Install / Use
/learn @googlebaba/StableCoxREADME
System Requirements
Hardware requirements
`Stable Cox' package requires only a standard computer with enough RAM to support the in-memory operations.
Software requirements
OS requirements
This package is supported for Linux. The package has been tested on the following system:
- Linux: Ubuntu 18.04
directly install StableCox via pip
pip install StableCox Tutorial on the package please see: https://pypi.org/project/StableCox/0.3/
Python Dependencies
'Stable Cox' mainly depends on the Python scientific stack.
lifelines=0.27.8
numpy=1.20.3
pandas=2.0.3
scikit-learn=1.3.0
Installation Guide
conda create -n Stable_Cox python=3.8
source activate Stable_Cox
pip install -r requirements.txt
- This takes several mins to build
Run demo
omics data
Stable Cox
python3 mRNA_HCC_OS.py --reweighting SRDO --paradigm regr --topN 10
Cox PH
python3 mRNA_HCC_OS.py --reweighting None --paradigm regr --topN 10
clinical data
Stable Cox
python3 clinical_lung_OS.py --reweighting SRDO --paradigm regr
Cox PH
python3 clinical_lung_OS.py --reweighting None --paradigm regr
simulated data
Stable Cox
python3 simulated.py --reweighting SRDO --paradigm regr
Cox PH
python3 simulated.py --reweighting None --paradigm regr
feature selection
Stable Cox
python3 simulated_fs.py --reweighting SRDO --paradigm regr --topN 5
Cox PH
python3 simulated_fs.py --reweighting None --paradigm regr --topN 5
- The expected running time is from several seconds to mins depends on the number of samples.
License
This project is licensed under the terms of the MIT license.
