Showing 2024Show all
2 papers · 1 filter
stat.ME2024
Heterogeneous Clinical Trial Outcomes via Multi-Output Gaussian Processes
Owen Thomas, Leiv Rønneberg
We make use of Kronecker structure for scaling Gaussian Process models to large-scale, heterogeneous, clinical data sets. Repeated measures, commonly performed in clinical research…
q-bio.QM2024
Permutation invariant multi-output Gaussian Processes for drug combination prediction in cancer
Leiv Rønneberg, Vidhi Lalchand, Paul D. W. Kirk
Dose-response prediction in cancer is an active application field in machine learning. Using large libraries of \textit{in-vitro} drug sensitivity screens, the goal is to develop a…