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MRC Biostatistics Unit

Summary

Solon is a Research Associate working with Oscar Rueda. He obtained his PhD from the Unit where his doctoral research focused on tailored Bayesian inference for risk prediction models. Before starting his PhD, he completed an MSc in Statistics at KU Leuven.

Solon's interests lie in developing statistical machine learning methods applied to medicine and healthcare. His research focuses on tailored model development, that is targeted model building for a specific task of interest, mostly prediction.

Solon is also looking at novel ways to incorporate liquid biopsies into the management of cancer. Liquid biopsies - the analysis of tumours using biomarkers circulating in fluids such as the blood - have the potential to change the way cancer is diagnosed, monitored, and treated.

He is particularly interested (risk) prediction modeling, (medical) decision making, computationally intensive methods, and translational genomics.

Selected Papers

  • Stavrinides, V., Norris, J. M., Karapanagiotis, S., Giganti, F., Grey, A., Trahearn, N., ... & PROMIS Group. (2022). Regional histopathology and prostate MRI positivity: a secondary analysis of the PROMIS trial. Radiology
  • Karapanagiotis, S., Benedetto, U., Mukherjee, S., Kirk, P. D., & Newcombe, P. J. (2021). Tailored Bayes: a risk modelling framework under unequal misclassification costs. Biostatistics
  • Stavrinides, V., Syer, T., Hu, Y., Giganti, F., Freeman, A., Karapanagiotis, S., ... & Emberton, M. (2021). False positive multiparametric magnetic resonance imaging phenotypes in the biopsy-naïve prostate: are they distinct from significant cancer-associated lesions? Lessons from PROMIS. European Urology.
  • Karapanagiotis, S., Pharoah, P. D., Jackson, C. H., & Newcombe, P. J. (2018). Development and external validation of prediction models for 10-year survival of invasive breast cancer. Comparison with PREDICT and CancerMath. Clinical Cancer Research.