Denniston, Alastair K

Tackling bias in AI health datasets through the STANDING TOGETHER initiative

Ganapathi, S., Palmer, J., Alderman, J. E., Calvert, M., Espinoza, C., Gath, J., Ghassemi, M., Heller, K., Mckay, F., Karthikesalingam, A., et al. (2022) · Nature Medicine

Ethics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

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Extension of the CONSORT and SPIRIT statements

Liu, X., Faes, L., Calvert, M. J., & Denniston, A. K. (2019) · The Lancet

Meta-analysis and systematic reviewsStatistical Methods in Clinical Trials

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Improving the quality of machine learning in health applications and clinical research

Mateen, B. A., Liley, J., Denniston, A. K., Holmes, C. C., & Vollmer, S. J. (2020) · Nature Machine Intelligence

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

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Concordance of randomised controlled trials for artificial intelligence interventions with the CONSORT-AI reporting guidelines

Martindale, A. P. L., Llewellyn, C. D., de Visser, R. O., Ng, B., Ngai, V., Kale, A. U., di Ruffano, L. F., Golub, R. M., Collins, G. S., Moher, D., et al. (2024) · Nature Communications

Meta-analysis and systematic reviewsArtificial Intelligence in Healthcare and Education

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The role of procurement frameworks in responsible AI innovation in the National Health Service: a multi-stakeholder perspective

Evans, T. D., Ahmad, O., Alderman, J. E., Bailey, G., Bannister, P., Barlow, N., Davison, N., Isaac, A., Kale, A. U., MacDonald, T., et al. (2025) · Frontiers in Health Services

Public Procurement and PolicyArtificial Intelligence in Healthcare and Education

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Innovating global regulatory frameworks for generative AI in medical devices is an urgent priority

Ong, J. C. L., Ning, Y., Liu, M., Ma, Y., Zhao, L., Singh, K., Chang, R. T., Vogel, S., Lim, J. C. W., Tan, I. S. K., et al. (2026) · npj Digital Medicine

Artificial Intelligence in Healthcare and EducationHealthcare Regulation

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