Content about “

medicine and health

”

Causal inference is the art of discerning cause and effect from data. Find out more in this introduction.

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.

To avoid full school closures in the next pandemic, or even epidemic, epidemiologists need crucial information from schools, students, and parents.

When a new infectious disease enters a population everything depends on who catches it — superspreaders or people with few contacts who don't pass it on.  We investigate the stochastic nature of the early stages of an outbreak.

With bird flu spreading through cattle herds in the US and infecting humans, the diseases poses a severe threat to wild life, poultry and also people. What can mathematical modelling do to help?