Explainers

Discover the science behind our AI diagnostic tool

Increasing the security of federated learning

MOSAIC is the world’s largest spatial multiomics dataset in oncology

Owkin combines cutting-edge machine learning and biology to advance drug discovery

Meet the people at the heart of AI-augmented healthcare

Prof Miriam Merad on the impact of building MOSAIC, the world’s largest spatial omics atlas in cancer

Data-driven prognostic covariates for adjustment to improve statistical power and broaden the eligibility criteria of randomized control trials

What is spatial omics and how it works, with Margaret Hoang, Associate Director of Research at NanoString

An open source federated learning software developed by Owkin for healthcare research

Meet FLamby – the world’s largest open-source federated learning-ready datasets designed to bridge the gap between federated learning theory and practice, while tackling multiple healthcare data modalities

A solution to help normalize real-world data distributed across multiple data centers in a federated manner, without compromising data privacy or security

Artificial intelligence may soon help doctors diagnose and treat diseases, including cancer and depression, based on the sound of a patient’s voice

A research project to develop new biomarkers to improve the targeting of antiangiogenic drugs

We select data-driven prognostic covariates for adjustment to improve statistical power without sacrificing power of randomized control trials

At Owkin we develop deep learning models to leverage crucial information captured in pathology images

We develop interpretable AI models to identify clinically relevant biomarkers from multimodal data, such as omics, imaging, histology and clinical data