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Publications

Bayesian inference for identifying tumour-specific cancer dependencies through integration of ex-vivo drug response assays and drug-protein profiling.

Xing H. and Yau C., (2024), BMC Bioinformatics, 25

Rarity: Discovering rare cell populations from single-cell imaging data.

Märtens K. et al, (2023), Bioinformatics

Sociodemographic characteristics and longitudinal progression of multimorbidity: A multistate modelling analysis of a large primary care records dataset in England.

Chen S. et al, (2023), PLoS Med, 20

Identifying factors associated with user retention and outcomes of a digital intervention for substance use disorder: a retrospective analysis of real-world data.

Günther F. et al, (2023), JAMIA Open, 6

The development of a core outcome set for studies of pregnant women with multimorbidity.

Lee SI. et al, (2023), BMC Med, 21

On the Difficulty of Predicting Engagement with Digital Health for Substance Use.

Günther F. et al, (2023), Stud Health Technol Inform, 302, 967 - 971

An atlas of genetic scores to predict multi-omic traits.

Xu Y. et al, (2023), Nature, 616, 123 - 131

Maternal and child outcomes for pregnant women with pre-existing multiple long-term conditions: protocol for an observational study in the UK.

Lee SI. et al, (2023), BMJ Open, 13

Polypharmacy during pregnancy and associated risk factors: a retrospective analysis of 577 medication exposures among 1.5 million pregnancies in the UK, 2000-2019.

Subramanian A. et al, (2023), BMC Med, 21

Protocol for development and validation of postpartum cardiovascular disease (CVD) risk prediction model incorporating reproductive and pregnancy-related candidate predictors.

Wambua S. et al, (2022), Diagn Progn Res, 6

Patient Derived Organoids Confirm That PI3K/AKT Signalling Is an Escape Pathway for Radioresistance and a Target for Therapy in Rectal Cancer.

Wanigasooriya K. et al, (2022), Front Oncol, 12

Rarity: Discovering rare cell populations from single-cell imaging data

Märtens K. et al, (2022)

Promises and challenges of adoptive T-cell therapies for solid tumours

Morotti M. et al, (2021), British Journal of Cancer, 124, 1759 - 1776

The Oxford Classic Links Epithelial-to-Mesenchymal Transition to Immunosuppression in Poor Prognosis Ovarian Cancers

Hu Z. et al, (2021), Clinical Cancer Research, 27, 1570 - 1579

Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension.

Cruz Rivera S. et al, (2020), Lancet Digit Health, 2, e549 - e560

Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension.

Liu X. et al, (2020), Lancet Digit Health, 2, e537 - e548

Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI Extension

Rivera SC. et al, (2020), BMJ, m3210 - m3210

Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI Extension

Liu X. et al, (2020), BMJ, m3164 - m3164

Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension

Cruz Rivera S. et al, (2020), Nature Medicine, 26, 1351 - 1363

Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension.

Liu X. et al, (2020), Nat Med, 26, 1364 - 1374

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