Latest News
Congratulations to Joel Nulsen on having his paper accepted in BMC Bioinformatics.
Genomic insights in settings where tumour sample sizes are limited to just hundreds or even tens of cells hold great clinical potential, but also present significant technical challenges. We previously developed the DigiPico sequencing platform to accurately identify somatic mutations from such samples.
We continue to contribute to the MUM-PREDICT and OPTIMAL projects over the last six months including:
Congratulations to Franziska Gunther on her collaborative work with Breaking Free Online on Identifying factors associated with user retention and outcomes of a digital intervention for substance use disorder: a retrospective analysis of real-world data which has been published in JAMIA Open.
Congratulations to Kaspar Martens on having his paper accepted at MLCB 2023.
Generative models for multimodal data permit the identification of latent factors that may be associated with important determinants of observed data heterogeneity. Common or shared factors could be important for explaining variation across modalities whereas other factors may be private and important only for the explanation of a single modality. Multimodal Variational Autoencoders, such as MVAE and MMVAE, are a natural choice for inferring those underlying latent factors and separating shared variation from private. In this work, we investigate their capability to reliably perform this disentanglement. In particular, wehighlight a challenging problem setting where modality-specific variation dominates the shared signal. Taking a cross-modal prediction perspective, we demonstrate limitations of existing models, and propose a modification how to make them more robust to modalityspecific variation. Our findings are supported by experiments on synthetic as well as various real-world multi-omics data sets. The paper is available on PMLR.
Congratulations to Franziska Gunther on her collaborative work with Breaking Free Online which was presented at MIE 2023: On the difficulty of predicting engagement with digital interventions for substance use disorders.
We are proud to have been part of a glittering array of publications arising from our contribution to the MUM-PREDICT projects over the last 12 months. The team also won the Health Data Research UK Team of the Year 2022 award:
Congratulations to group members Charles Gadd, Woojung Kim and Dominic Danks on the following papers accepted at ML4H and NeurIPS:
In a collaboration led by Carles Foguet and Mike Inouye, Christopher Yau contributed to Genetically personalised organ-specific metabolic models in health and disease which has been published in Nature Communications.
What am I doing?
My name is Christopher Yau and I am Professor of Artificial Intelligence at the University of Oxford and Health Data Research UK.
I am carrying out a survey of UK PhD students who are working in any area of data science and I need your help! We hope to get survey responses from over 300 PhD students so please help us by sparing 10-15 minutes of your time to answer some questions.
