Getting started with the hdnom app
This web application helps you build penalized Cox models for high-dimensional data with survival outcomes. All the 9 types of model included in the hdnom package are supported. It streamlined the process of nomogram building, model validation, calibration, comparison, and reproducible report generation — all done inside your web browser.
Please read the data privacy policy first before you start using this app.
The following workflow is recommended:
- Click Data to upload your dataset;
- Specify the parameters for building models in the Nomogram tab;
- Validate and calibrate the built model internally using Internal Validation and Internal Calibration under the Model Validation tab;
- Perform Kaplan-Meier analysis and log-rank test for the risk groups of internal calibration using Kaplan-Meier Analysis for Internal Calibration;
- (Optional) Validate and calibrate the built model with external datasets using External Validation and External Calibration under the Model Validation tab;
- (Optional) Perform Kaplan-Meier analysis and log-rank test for the risk groups of external calibration using Kaplan-Meier Analysis for External Calibration;
- (Optional) Compare the models via by Validation and by Calibration under the Model Comparison tab;
- (Optional) Predict overall survival probability for new samples based on the built model using the Prediction tab;
- Finally, you will be able to download the PDF/HTML/Word report containing the computation results, and the R model object in the Report tab.
Notes:
- To generate the basic report, please (at least) do step 1, 2, 3, and 4;
- To generate the external validation report, please do step 1, 2, 5, and 6;
- To generate the model comparison report, please do step 1 and 7;
- To download the R model object, please do step 1 and 2.
- After downloaded the model object, it might be interesting to try the hdnom application maker to make your own nomogram-based online prediction app.
Citation
To cite the hdnom package or the web application in your publications,
please click here to view the most recent reference to use.
Feedback
If you have any questions, suggestions, or ideas about the web application, please feel free to let us know:
© 2015 - 2016 Miaozhu Li & Nan Xiao · The hdnom Project · Data Privacy Policy