Andres Tamm

I am a health data scientist and researcher working on applying machine learning methods to electronic health records to improve the understanding of cancer and cancer care. I am supervised by Dr Brian Nicholson as part of the cancer group  and by professor Eva Morris (Nuffield Department of Population Health, Big Data Institute). I am particularly interested in optimising the faecal immunochemical test (FIT) for colorectal cancer referrals from primary to secondary care, understanding variations in patient pathways, and conducting reproducible and scalable research with electronic health records.

I recently submitted my thesis in the EPSRC Centre for Doctoral Training in Health Data Science. I explored whether the FIT test can be combined with routinely collected data to increase its precision, developed lightweight text processing tools to extract cancer staging scores from free text clinical reports to facilitate cancer research, and explored methods of automatically clustering patient pathways to study variations in treatment. I also have a highly interdisciplinary background, having previously studied gene technology (BSc) and psychology (BA) in Estonia, and psychological research with substantial statistics component (MSc) in the University of Edinburgh. I have worked with a variety of datasets, including single-cell RNA sequencing, heart rate time series, and functional magnetic resonance imaging.

When I am not engaged in research, I enjoy dancing, mindfulness, and yoga.