In a network, not all nodes are created equal. Find out about three neat ways of measuring the importance of a node.
Should a life-saving, but expensive, cancer drug be made available on the NHS even though it only benefits very few people? We spoke to Joe Hilton, a health economist, to understand more about how difficult decisions like this one are made.
Causal inference is the art of discerning cause and effect from data. Find out more in this introduction.
A research programme at the Isaac Newton Institute is investigating how to best discern cause and effect from data.
Infectious diseases in hospitals cost lives and money. How can we best understand them?
Find out how deep learning can help improve the images produced by MRI, CT and PET scans, making patients more comfortable and cutting NHS waiting lists.
Disruptions to public services are annoying – but that data about these disruptions is more useful than you might think.
How do mathematicians help policy makers make the best decisions?
A digital heart might sound like science fiction, but these personalised mathematical descriptions of patients' hearts are already being put to the test.
Can topological data analysis create a revolution in the life sciences?
Find out about a pioneering new project which builds mathematical models together with the people who are affected.
Find out about a pioneering new project which builds mathematical models together with the people who are affected by them.
