We are a multi-disciplinary team of researchers who collaborate on the development of methods to make precision medicine cost effective, efficient, sustainable, trustworthy and reliable.
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Our track record speaks for itself.
McLachlan, S., Dube, K., Buchanan, D., Lean, S., Johnson, O., Potts, H., Gallagher, T., Marsh, W., & Fenton, N. (2017) Learning Health Systems: The research community awareness challenge BCS Journal of Innovation in Health Informatics, 25(1). DOI: http://dx.doi.org/10.14236/jhi.v25i1.981
McLachlan, S., Dube, K., Gallagher, T., Daley, B., & Walonoski, J. (2018) The ATEN Framework for Creating the Realistic Synthetic Electronic Health Record. Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies, HEALTHINF 2018
McLachlan, S., Neil, M., Dube, K., Bogani, R., Fenton, N., & Schafer, B. (2022). Smart automotive technology adherence to the Law: (De)Constructing Road Rules for Autonomous System Development, Verification and Safety. Journal of Law and Information Technology. http://doi.org/10.1093/ijlit/eaac002
McLachlan, S., Johnson, O., Dube, K., Buchanan, D., Potts, H.W.W., Gallagher, T., & Fenton, N. (2019). A framework for analysing learning health systems: Are we removing the most impactful barriers? Journal of Learning Health Systems. DOI: 10.1002/lrh2.10189
Daley, B., Hitman, G.A., Fenton, N., & McLachlan, S. (2019) Assessment of the quality and content of national and international guidelines on the identification and management of Diabetes in Pregnancy: An AGREE II Study. BMJ Open, e:027285.
Neil, M., Fenton, N., Osman, M., & McLachlan, S. (2020). Bayesian network analysis of COVID-19 data reveals higher infection prevalence rates and lower fatality rates than widely reported. Journal of Risk Research, 23(7-8) https://doi.org/10.1080/13669877.2020.1778771
Kyrimi, E., Dube, K., Fenton, N., Fahmi, A., Neves, M., Marsh, W., & McLachlan, S. (2020). Bayesian Networks in Healthcare: What is preventing their adoption? Artificial Intelligence in Medicine, 116. https://doi.org/10.1016/j.artmed.2021.102079
Kyrimi, E., McLachlan, S., Dube, K., Neves, M. R., Fahmi, A., & Fenton, N. (2020). A Comprehensive Scoping Review of Bayesian Networks in Healthcare: Past, Present and Future. Artificial Intelligence in Medicine, 116. https://doi.org/10.1016/j.artmed.2021.102108
McLachlan, S., Dube, K., Kyrimi, E., & Fenton, N. (2019). LAGOS: Making sense of Learning Health Systems and how they can integrate with Patient Care. BMJ Health and Care Informatics (BMJHCI) 26(1).
Kyrimi E, Marsh W (2016) ‘A Progressive Explanation of Inference in Hybrid Bayesian Networks for Supporting Clinical Decision Making’, in the Eighth International Conference on Probabilistic Graphical Models, vol. 52, pp. 275-286, 2016.
Daley, B., Ni’Man, M., Neves, M., Bobby, M., Marsh, W., Fenton, N., Hitman, G. & McLachlan, S. (2021). mHealth Apps for Gestational Diabetes Mellitus that provide Decision Support or Artificial Intelligence: A Scoping Review. Diabetic Medicine. 39(1), e14735. https://doi.org/10.1111/dme.14735
Fenton, N., Neil, M., McLachlan, S., & Osman, M. (2021). Misinterpreting statistical anomalies and risk assessment when analysing COVID-19 deaths by ethnicity. Significance, 18(2). https://www.significancemagazine.com/701
McLachlan, S., Kyrimi, E., Dube, K., Fenton, N., & Webley, L. (2022). Lawmaps: Enabling Legal AI development through Visualisation of the Implicit Structure of Legislation and Lawyerly Process. Journal of Artificial Intelligence and Law. https://doi.org/10.1007/s10506-021-09298-0
McLachlan, S., Potts, H.W.W., Dube, K., Buchanan, D., Lean, S., Gallagher, T., Johnson, O., Daley, B., Marsh, W., & Fenton, N. (2018) The Heimdall Framework for supporting characterisation of Learning Health Systems. Journal of Innovation in Health Informatics, 25(2). DOI: http://dx.doi.org/10.14236/jhi.v25i2.996