IMSCO, Lake Tahoe, Nevada (2019).

I had the pleasure to present my work on OncoCast at the International Symposium on Mathematical and Computational Oncology (IMSCO) in 2019. My talk summarised the delayed entry issue found in genomic survival dataset and how I modified well known machine learning algorithms to account for this bias. Further explaining the underlying mechanisms of the ensemble learning framework of OncoCast, simulation results and a real data example. Slides can be found below:

Axel S. Martin
Axel S. Martin
PhD Student

My research interests include developing doubly-robust estimator theory for transportability and generalization of treatment specific survival curves, and developing doubly-robust estimators in the context of repeated continuous/factorial exposures effects.