Reynolds DJ, Mountain S, Bartle V, Remfry E, Barnes MR, Reynolds NJ, Thompson A, AI MULTIPLY. Targeting everyday decision makers in research: early career researcher and patient and public involvement and engagement collaboration in an AI-in-healthcare project. doi.org/10.1186/s40900-025-00753-9. Paper.

Flowers C, Naveed S, Reynolds N, Barnes MR.  Setting up for Success: Insights from a Project Manager in AI-Driven Healthcare Research. doi: 10.5281/zenodo.15676720 Abstract.

Mountain S, Thompson A, Reynolds N, Reynolds DJ, Barnes MR. Democratising research through PPIE and ECR collaboration in an AI-in-Healthcare research project. Participatory AI Research & Practice Symposium in Paris. Abstract

Remfry E, Morgado De Queiroz S, Mathur R, Barnes MR, Thomson A, Reynolds DJ. Using arts-based methods to include the perspectives of underrepresented groups in the development of artificial intelligence tools in healthcare research.  Abstract.

Reynolds N, Bartle V, Barnes MR. Summary of NIHR AIM funded AI-MULIPLTY consortium. Abstract.

Richards K, et al? Understanding the pattern of prescribed medication. Abstract.

Thompson A, Bartle V, Hanratty B, Remfry E, Reynolds N, Barnes MR.  Evaluating public and patient involvement and engagement in AI-driven healthcare research project. Abstract.

Remfry E, Angdembe A.  Studying the longitudinal dynamics of multimorbidity in electronic healthcare records: a rapid review of machine learning methods.

Richards K, Fleetwood K, Prigge R, Missier P, Barnes M, Reynolds NJ, … Seth Sohan.  Probabilistic Modelling of Multiple Long-Term Condition Onset Times. Arxiv. doi.org/10.48550/arXiv.2412.07657

Van Blarikom E, Fudge N, Swinglehurst D. Multimorbidity as chronic crisis: ‘Living on’ with multiple long-term health conditions in a socially disadvantaged London borough. Sociology of health & illness. 46(4), pp. 608-626. doi: 10.1111/1467-9566.13729

Samuel M, Park RY, Eastwood SV, Eto F, Morton CE, Stow D, … OpenSAFELY Collaborative. Weight trends among adults with diabetes or hypertension during the COVID-19 pandemic: an observational study using OpenSAFELY. The British journal of general practice : the journal of the Royal College of General Practitioners, 74(748), pp. e767-e776. doi: 10.3399/bjgp.2023.0492

Calero-Diaz.H, Hamad.R, Atallah. C, Casement. J, Canoy.D, Reynolds.N.J.  Interpretable and robust hospital readmission predictions from Electronic Health Records. IEEE Explore. doi: 10.1109/BigData59044.2023.10386820

Dambha-Miller H, Farmer A, Nirantharakumar K, Jackson T, Yau C, Walker L, … Guthrie B. Artificial Intelligence for Multiple Long-term conditions (AIM): A consensus statement from the NIHR AIM consortia. doi.org/10.3310/nihropenres.1115210.1

Eto F, Samuel M, Henkin R, Mahesh M, Ahmad T, Angdembe A, … Mathur R.  Ethnic differences in early onset multimorbidity and associations with health service use, long-term prescribing, years of life lost, and mortality: A cross-sectional study using clustering in the UK Clinical Practice Research Datalink.PLoS medicine. 20(10), pp. e1004300. doi: 10.1371/journal.pmed.1004300

Henkin.R, Barnes M.R.  visxhclust: An R Shiny package for visual exploration of hierarchical clustering. The Journal of Open Source Software. doi.org/10.21105/joss.04074

Rao S, Nazarzadeh M, Canoy D, Li Y, Huang J, Mamouei M, … Rahimi K.  Sodium-based paracetamol: impact on blood pressure, cardiovascular events, and all-cause mortality. European heart journal, 44(42), pp. 4448-4457. doi: 10.1093/eurheartj/ehad535

Kremer R, Raza S, Eto F, Casement J, Atallah C, Finer S, … Missier P.  Tracking trajectories of multiple long-term conditions using dynamic patient-cluster associations. doi: 10.1109/bigdata55660.2022.10021034

Van Blarikom E, Fudge N, Swinglehurst D. The emergence of multimorbidity as a matter of concern: a critical review. BioSocieties, (3), doi: 10.1057/s41292-022-00285-5