News
Latest updates from the AI for Oncology Lab.

New publication about breast cancer primary treatment response assessment and prediction
Primary systemic therapy (PST) is the treatment of choice in patients with locally advanced breast cancer and is nowadays also often used in patients with early-stage breast cancer. In our review, we critically discuss the literature on AI-based PST response prediction.

New preprint about Constrained Empirical Risk Minimization
Our latest research provides an innovative solution to the challenge of enforcing constraints on deep neural networks. We reframe the constraints on a network as an ordinary risk minimization problem on a Riemannian manifold.

STAPLER: a language model to predict TCR–pMHC reactivity
Our latest paper introduces STAPLER, a cutting-edge language model that significantly enhances TCR-pMHC reactivity prediction, outperforming previous models in the field.
A deeper understanding of TCR-pMHC interactions is key to unlocking the potential of personalized immunotherapies and expanding our knowledge of the immune system.

GPU cluster expanded with gaia and galileo
We have added another 8xA6000 server (galileo) and a CPU server (gaia) to our Kosmos cluster. Kosmos now consists out of 70 GPUs, more than 1100 CPU cores, 6TB RAM and 1PB NAS.