Dr Oleg Blyuss

Oleg Blyuss is Reader in Data Science and Statistics at Queen Mary University of London.

His work revolves around the application of machine learning and AI approaches to combine complex multi-omic data, including longitudinal analytes, into a predictive modelling tool. He developed the Method of Mean Trends (MMT) algorithm, which analyzes trend indices in serial measurements to estimate the risk of ovarian cancer. He also co-supervised the development of PancRISK, a machine learning approach that combines a panel of urine biomarkers and has demonstrated the potential to discriminate early-stage pancreatic cancer patients from healthy controls.

Oleg’s other research interests include predictive modelling of the progression of prostate cancer patients undergoing active surveillance, as well as the application of GAN methodology to discriminate high-risk cysts for the early detection of pancreatic cancer.

Follow Oleg on Twitter @BlyussOleg