Machine learning – a field of artificial intelligence that uses statistical techniques to enable computer systems to ‘learn’ from data – can be used to analyse electronic health records and predict the risk of emergency hospital admissions, a new study from The George Institute for Global Health at the University of Oxford has found.

People with irregular and abnormally fast heart rates caused by a condition called atrial fibrillation could be at a greater risk of stroke and bleeding because they are not receiving optimal treatment, warn scientists from UCL and The University of Hong Kong (HKU).

Researchers have developed a model that predicts which of the viruses that can jump from animals to people can also be transmitted from person to person—and are therefore possible sources of human diseases.

A single bacterial cell on its own is vulnerable to attack and like many living things they can benefit from safety in numbers. But bacteria take communal living to a whole new level, forming veritable civilizations - the bacterial biofilm.

The rate at which new drugs are discovered is in decline, and computer-aided drug design has not produced the radical change in the success of candidate drugs the pharma industry anticipated. Artificial intelligence (AI)-based approaches are the new hope for revolutionizing the drug discovery process. But are these, as computer-aided drug design was, an over-hyped time bomb waiting to be found out? Or is it truly a revolution on the cusp of realizing its promise?

As part of the host-pathogen arms race, viruses are continually evolving to evade the host immune response, be it from previous infection or immunity acquired through vaccination. Here we take a look at the processes of antigenic drift and antigenic shift.