Papers
Publications
Remfry, E., Tomba, G., Barnes, M.R. et al. What influences patients’ perspectives on the fairness of AI decision-making tools in healthcare? A cross sectional survey in the UK. BMC Med Inform Decis Mak 2026. https://doi.org/10.1186/s12911-026-03906-2
Remfry E, Conway A, Adatia N, et al. Navigating the regulatory boundary: a sandbox approach to validating scope expansion in LLM-based ambient AI scribes. BMJ Innovations. 2026. doi: 10.1136/bmjinnov-2026-001648
Henkin R^, Remfry E^, Reynolds DJ, Clinch M, Barnes MR. “We’ll have to see how it works”: An interview study to understand collaborative practices in interdisciplinary artificial intelligence and healthcare research. 2026. PLOS ONE 21(7): e0354358. https://doi.org/10.1371/journal.pone.0354358
Remfry E, Reynolds DJ, de Queiroz SM, Social Action For Health, Mathur R, Barnes MR, Thomson A; AI‐Multiply PPIE Group and AI‐Multiply. Using Arts-Based Methods to Involve People Living in Tower Hamlets With Multiple Long-Term Conditions in the Development of Artificial Intelligence Tools in Healthcare Research. Health Expect. 2026 Apr;29(2):e70621. doi: 10.1111/hex.70621.
Remfry E, Chaturvedi J, Markham S, Ford E, Ramasawmy M. Co-designing animated videos to explain large language models and their use in healthcare and research. Front Digit Health. 2026 Apr 13;8:1758463. doi: 10.3389/fdgth.2026.1758463.
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 electronic healthcare records facilitates transfer learning. International Conference on Artificial Intelligence in Healthcare.
Orazumbekova, B.^, Remfry, E.^, Henkin, R., Barnes, M. R., and Mathur, R. Sex differences in risk factors for micro- and macro-vascular complications in early and usual onset Type 2 Diabetes. European Association for the Study of Diabetes (EASD). 2025.
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
Remfry, E., and Henkin, R. (2026). Interoperability of standardised electronic healthcare records facilitates transfer learning of clinical language models.
Reynolds, DJ, Remfry, E., Swinglehurst, D., Fudge, N,. Protocol for General Practice Automation and Innovation with AI-enabled ambient scribes (GAIA): a qualitative narrative study of patients’ and GPs’ experiences.
^joint first author