Machine learning of genomic features in organotropic metastases stratifies progression risk of primary tumors

Abstract

The location and timing of metastasis are still fundamentally unpredictable. Here the authors present the Metastatic Network model, a machine learning framework that integrates clinical data and DNA alterations to predict the risk of metastasis to specific organs as well as clinical outcomes