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Search results (151)

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Transcriptomic analysis of tissue-resident memory T cells of the fallopian tube reveals a precursor immune surveillance network for ovarian cancer prevention.

Wang L. et al, (2026), Nature communications

MIND: multimodal integration with neighbourhood-aware distributions.

Xing H. and Yau C., (2026), Nature communications

Imputation Free Deep Survival Prediction with Conditional Variational Autoencoders.

Hong N. et al, (2026), Journal of healthcare informatics research, 10, 275 - 298

Understanding the spatial determinants of the Oxford Classic prognostic signature for high-grade serous ovarian cancer.

Stihi A. and Yau C., (2026), Communications medicine

Investigating the effect of climate and air pollution on prescription uptake in the England.

Tolladay J. and Yau C., (2026), BMC public health

SurvivEHR: a competing risks, time-to-event foundation model for multiple long-term conditions from primary care electronic health records.

Gadd C. et al, (2026), NPJ digital medicine

Untangling biological complexity: A deep learning approach to separating multiple signals in single-cell data.

Yau C., (2026), Cell genomics, 6

Supplementary Figure S2 from Oxford Classic–Defined EMT Risk Stratification of High-Grade Serous Ovarian Cancer for Guiding Treatment Decisions

Rai L. et al, (2026)

Data from Oxford Classic–Defined EMT Risk Stratification of High-Grade Serous Ovarian Cancer for Guiding Treatment Decisions

Rai L. et al, (2026)

Supplementary Figure S1 from Oxford Classic–Defined EMT Risk Stratification of High-Grade Serous Ovarian Cancer for Guiding Treatment Decisions

Rai L. et al, (2026)

Supplementary Figure S3 from Oxford Classic–Defined EMT Risk Stratification of High-Grade Serous Ovarian Cancer for Guiding Treatment Decisions

Rai L. et al, (2026)

Supplementary Figure S4 from Oxford Classic–Defined EMT Risk Stratification of High-Grade Serous Ovarian Cancer for Guiding Treatment Decisions

Rai L. et al, (2026)

Supplementary Figure S5 from Oxford Classic–Defined EMT Risk Stratification of High-Grade Serous Ovarian Cancer for Guiding Treatment Decisions

Rai L. et al, (2026)

Supplementary Table S1 from Oxford Classic–Defined EMT Risk Stratification of High-Grade Serous Ovarian Cancer for Guiding Treatment Decisions

Rai L. et al, (2026)

Oxford Classic-Defined EMT Risk Stratification of High-Grade Serous Ovarian Cancer for Guiding Treatment Decisions.

Rai L. et al, (2026), Clinical cancer research : an official journal of the American Association for Cancer Research, 32, 188 - 202

Development and validation of a postpartum cardiovascular disease risk prediction model in women incorporating reproductive and pregnancy-related predictors

Wambua S. et al, (2025), BMC Medicine, 23

araCNA: somatic copy number profiling using long-range sequence models.

Visscher E. and Yau C., (2025), NAR genomics and bioinformatics, 7

Development and validation of a postpartum cardiovascular disease risk prediction model in women incorporating reproductive and pregnancy-related predictors.

Wambua S. et al, (2025), BMC medicine, 23

Incorporation of Patient and Public Involvement in Statistical Methodology Research: Summary of Workshop Proceedings.

Smith A. et al, (2025), Statistics in medicine, 44

GPerturb: Gaussian process modelling of single-cell perturbation data.

Xing H. and Yau C., (2025), Nature communications, 16

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