Abstract
Developing fair and unbiased models is important for good scientific practice and clinical utility. This paper delves into the specific biases associated with artificial intelligence (AI) in neuroimaging research, and highlights the structural issues that underpin them. We propose a range of mitigation strategies, encompassing both behavioural and technical considerations. By recognising these challenges, we can encourage more accurate and equitable insights into neuroimaging research.
S. A. Martin, F. Biondo and B. Taylor—These authors contributed equally.
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Acknowledgements
We would like to thank members of the Centre for Medical Image Computing, UCL and the Dementia Research Centre, UCL, for interesting and insightful discussions which helped shape this work.
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Martin, S.A., Biondo, F., Cole, J.H., Taylor, B. (2023). Brain Matters: Exploring Bias in AI for Neuroimaging Research. In: Wesarg, S., et al. Clinical Image-Based Procedures, Fairness of AI in Medical Imaging, and Ethical and Philosophical Issues in Medical Imaging. CLIP EPIMI FAIMI 2023 2023 2023. Lecture Notes in Computer Science, vol 14242. Springer, Cham. https://doi.org/10.1007/978-3-031-45249-9_11
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