Federated Learning: How to Put Patient Privacy First in Healthcare AI

Accessing the volume and diversity of data required for robust and precise machine learning is currently one of the biggest limiting factors to the use of artificial intelligence in healthcare. Health data is private, sensitive, often confidential, and can only be processed in compliance with strict institutional, national and federal regulations. This presentation explores how federated learning technology can be used to overcome this challenge and allow developers to access healthcare data for use in machine learning algorithms with full regulatory compliance. Owkin brings this new learning paradigm to all healthcare stakeholders, unlocking the potential for safer, better and more effective medical research with its federated learning platform Owkin Connect.