Deep learning models for predicting the survival of patients with chondrosarcoma based on a surveillance, epidemiology, and end results analysis
Data preprocessing is handled by R code: DataPreprocessing.R
Model construction, hyperparameters tuning and evaluation are handled with pysurvival, scikit-learn and lifelines packages: ModelDevelopmentWithoutTuningOutput.ipynb
Web application based on streamlit package: app.py
The original data read in R code is not provided in this repository and needs to be extracted in the SEER database according to inclusion criteria (AYA site recode 2020 Revision = 4.2 Chondrosarcoma)
To reproduce this study, first run the following codes to install packages:
git clone https://github.com/WHUH-ML/Chondrosarcoma.git
pip install -r requirements.txt
Then run ModelDevelopmentWithoutTuningOutput.ipynb in Jupyter Notebook.
Run streamlit run app.py
in terminal to open the web application locally.