Federated AI supports three main tasks: training models across separate data systems, checking how those models perform in different environments and running privacy-safe analyses to guide development ...

Federated Learning is a decentralised and privacy-friendly form of machine learning. This means that there is no need for a central database to hold all of the sensitive data, so these data cannot be ...

The Owkin teams worked with researchers across four hospitals, and were able to train the federated learning model on clinical information and pathology data from 650 patients.

Adaptive AI platforms for SOCs offer real-time alert triage, faster response times, and full-spectrum security coverage.

By using data from multiple sources, federated learning improves the generalizability and robustness of AI models—enabling the inclusion of diverse patient populations, which is crucial for ...

A federated learning (FL) model demonstrated great promise in the binary classification of nevi and invasive melanomas while showcasing the benefits that artificial intelligence ...

In research published in Nature Medicine today, AI biotech company Owkin has demonstrated for the first time that federated learning (FL) can be used to train deep learning models on data from ...