Federated Learning for Healthcare – Collaborative AI without Exposing Patient Data

11:20-11:40, January 28

Talk/ Overview

Artificial Intelligence and in particular Deep Learning has become an essential technique for various application fields – including healthcare. One of the core requirements for training a reliable AI algorithm is the availability of an extensive and diverse data set. This, however, poses a major challenge for medical applications: patient data needs to be protected and cannot easily be shared. In this talk we will discuss Federated Learning which addresses this problem and enables to learn collaboratively across several institutions while keeping the patient data save.

Talk/ Speakers

Nicola Rieke

Senior Deep Learning Solution Architect – Healthcare, NVIDIA

AMLD / Global partners