Treanor, Darren

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The STARD-AI reporting guideline for diagnostic accuracy studies using artificial intelligence

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Developing a reporting guideline for artificial intelligence-centred diagnostic test accuracy studies: the STARD-AI protocol

Sounderajah, V., Ashrafian, H., Golub, R. M., Shetty, S., De Fauw, J., Hooft, L., Moons, K., Collins, G., Moher, D., Bossuyt, P. M., et al. (2021) · BMJ Open

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Artificial Intelligence in Digital Pathology: A Systematic Review and Meta-Analysis of Diagnostic Test Accuracy

McGenity, C., Clarke, E. L., Jennings, C., Matthews, G., Cartlidge, C., Freduah-Agyemang, H., Stocken, D. D., & Treanor, D. (2024) · npj Digital Medicine

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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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The ethical challenges of artificial intelligence‐driven digital pathology

McKay, F., Williams, B. J., Prestwich, G., Bansal, D., Hallowell, N., & Treanor, D. (2022) · The Journal of Pathology: Clinical Research

Artificial Intelligence in Healthcare and EducationAI in cancer detection

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Public governance of medical artificial intelligence research in the UK: an integrated multi-scale model

McKay, F., Williams, B. J., Prestwich, G., Treanor, D., & Hallowell, N. (2022) · Research Involvement and Engagement

Ethics and Social Impacts of AIEthics in Clinical Research

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