Tool to build a patient classifier using similarity networks

This project is maintained by The Bader Lab, U. Toronto


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?

Reference: Pai S et al. netDx: interpretable patient classification using integrated patient similarity networks. Molecular Systems Biology (2019) 15, e8497

Questions? Contact Shraddha Pai,