- Kyrimi, E. et al (2024). Explainable AI in healthcare: Fundamentals challenge.
- Pisirir, E., Wohlgemut, J., Kyrimi, E. et al. (2023). A Process for Evaluating Explanations for Transparent and Trustworthy AI Prediction Models. IEEE 11th International Conference on Healthcare Informatics (ICHI), Houston, TX, USA, pp. 388-397, DOI: 10.1109/ICHI57859.2023.00058.
- Kyrimi, E., McLachlan, S., Dube, K., Neves, M.R., Fahmi, A. & Fenton, N. (2021). A comprehensive scoping review of bayesian networks in healthcare: Past, present and future. Artificial Intelligence in Medicine, 117, 102108. DOI: 10.1016/j.artmed.2021.102108
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- Kyrimi, E., Neves, M., McLachlan, S., Neil, M., Marsh, W., & Fenton, N. (2020). Medical Idioms: Reasoning patterns to develop medical Bayesian Networks. Journal of Biomedical Informatics, DOI: 10.1016/j.jbi.2020.103495
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- Delphi study questionnaires Round 1 and Round 2
Explainable AI to ensure trust in clinical Decision Support Systems