Confederated Machine Learning on Horizontally and Vertically Separated Medical Data for Large-Scale Health System Intelligence

no code implementations • ICLR 2020 • Dianbo Liu, Kathe Fox, Griffin Weber, Tim Miller

We proposed and evaluated a confederated learning to training machine learning model to stratify the risk of several diseases among when data are horizontally separated by individual, vertically separated by data type, and separated by identity without patient ID matching.

BIG-bench Machine Learning Federated Learning