Papers
Publications
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. Res Involv Engagem. 2025 Aug 19;11(1):100. doi: 10.1186/s40900-025-00753-9.
Thompson A, Bartle V, Remfry EA, Reynolds DJ, Barnes MR, Reynolds NJ, Hanratty B. Public and Patient Involvement in Artificial Intelligence and Big Data Healthcare Research: An Exploration of Issues and Challenges Within the AI-Multiply Project. Health Expect. 2025 Dec;28(6):e70490. doi: 10.1111/hex.70490.
Guler, G., Remfry, E., Kherroubi Garcia, I., Barrow, N. & Duarte, T. (2024) Grassroots and non-profit perspectives on generative AI. Joseph Roundtree Foundation, https://www.jrf.org.uk/ai-for-public-good/grassroots-and-non-profit-perspectives-on-generative-ai
Remfry, E., Ardissino, M., McCracken, C., Szabo, L., Neubauer, S., Harvey, N.C., Mamas, M.A., Robson, J., Petersen, S.E. and Raisi-Estabragh, Z., 2024. Sex-based differences in risk factors for incident myocardial infarction and stroke in the UK Biobank. European Heart Journal-Quality of Care and Clinical Outcomes, 10(2), pp.132-142.
Andersen, Z.J., Zhang, J., Jørgensen, J.T., … Remfry, E., .. Lim, Y. 2022. Long-term exposure to air pollution and mortality from dementia, psychiatric disorders, and suicide in a large pooled European cohort: ELAPSE study. Environment international, 170, p.107581.
Gold, N., Yau, A., Rigby, B., Dyke, C., Remfry, E.A. and Chadborn, T., 2021. Effectiveness of digital interventions for reducing behavioral risks of cardiovascular disease in nonclinical adult populations: systematic review of reviews. Journal of medical Internet research, 23(5), p.e19688.
Remfry, E. “The Cost of Losing Touch.” Coronatanker: Studenterperspektiver Fra En Lockdown, by Kristian Engberg, Forlaget 21:34, 2020, pp. 162–166.
Accepted Conference Papers/Posters
Elizabeth Remfry and Rafael Henkin (2025). Interoperability of standardised electronichealthcare records facilitates transfer learning. International Conference on Artificial Intelligence in Healthcare.
Elizabeth Remfry, Jaya Chaturvedi, Sarah Markham, Elizabeth Ford and Mel Ramasawmy (2025). Co-design of an Animated Video to Explain Large Language Models and Their Use in Research. 8th Healthcare Text Analytics Conference. WINNER OF BEST POSTER.
Remfry, E., Henkin, R., Barnes, M.R. and Naik, A., 2024. Exploring Long-Term Prediction of Type 2 Diabetes Microvascular Complications. Machine Learning for Health. arXiv preprint arXiv:2412.01331.
Remfry, E., Henkin, R., Awan, Z., Mathur, R., Barnes, M.R. and Naik, A., 2024. Exploring Fairness in Long-Term Prediction of Type 2 Diabetes Microvascular Complications. Advancements In Medical Foundation Models: Explainability, Robustness, Security, and Beyond. Neural Information Processing Systems.
Under review
Henkin, R.^, Remfry, E.^, Reynolds, D.J., Clinch, M. and Barnes, M.R., 2024. Investigating Collaborative Data Practices: a Case Study on Artificial Intelligence for Healthcare Research. arXiv preprint arXiv:2311.18424v2
Remfry, E., Reynolds, D.J., Morgado de Queiroz, S., Social Action for Health, Mathur, R., Barnes, M.r., Thomson, A., AI-MULTIPLY PPIE Group and the AI-MULTIPLY Consortium, 2025. Using arts-based methods to include the perspectives of underrepresented groups in the development of artificial intelligence tools in healthcare research.
Remfry, E.^, Chaturvedi, J.^, Markham, S., Ford, E., and Ramasawmy, M. (2025) Co-designing animated videos to explain large language models and their use in healthcare and research.
^joint first author