Home

Welcome to the netDx wiki!

netDx is a patient classifier algorithm that can integrate several types of patient data into a single model. It does this by converting each type of data into a view of patient similarity; i.e. by converting the data into a graph in which more similar patients are tightly linked, while less similar patients are not so tightly linked.

What do you want to do?

• Learn how netDx works
• Get the software (link to main page of this repo)
• See netDx in action with R vignettes and notebooks
• Learn to design effective predictors and use netDx with the user manual (in active development; feedback welcome!)

Reference: Pai S, Hui S, Isserlin I, Shah MA, Kaka H, and GD Bader. netDx: interpretable patient classification using integrated patient similarity networks. Molecular Systems Biology (2019) 15, e8497

Questions? Contact Shraddha Pai.