Topics: Statistical methods for multi-state models, colorectal cancer screening and surveillance
Eddymurphy holds two Master’s degrees in Mathematical Sciences and Computational Engineering from the African Institute for Mathematical Sciences and LUT University, Finland, respectively. He completed his PhD at Amsterdam University Medical Centers, Vrije Universiteit Amsterdam. His thesis, titled "Modelling cancer surveillance data", focused on the development of novel statistical methods for estimating the multi-state process of cancer progression on the basis of surveillance data with censoring due to intervention. These methods aim to accurately estimate both the average-population and personalized risks of developing cancer precursor lesions and cancer.
His current research focuses on developing time-to-event microsimulation models to optimize colorectal cancer surveillance strategies for individuals with Lynch syndrome, using estimates derived from multi-state survival models applied to real-world cancer surveillance data.