New network brings together researchers on AI in health

In just a few years, artificial intelligence has become one of the most talked-about fields in health research. Around the world, researchers now use everything from simple tools that assist with data collection and writing to advanced models that can analyse vast amounts of health data to support the diagnosis and treatment of disease.

Health is no exception to this development. In response, the faculty is establishing the HealthAI research network to bring together researchers who work with – or simply have an interest in – the field.

“More and more of us are working with AI in one way or another – either by developing models ourselves or by researching the use of existing ones. We need a place where we can share experiences, spar with each other and find new collaborators,” says Professor Stine Sofia Korreman from the Department of Clinical Medicine, who co-chairs the new network with Associate Professor Adam Hulman.

AI has entered health research

According to Adam Hulman, who is affiliated with the Department of Public Health and Steno Diabetes Center Aarhus, the growing amounts of data available to researchers are a key driver.

“Developments have moved extremely fast. AI is no longer just for those who work directly with developing methods. It is now on the radar across many areas of health research,” he explains.

“Today, we can link many different types of clinical data and use machine learning to analyse them. Medical image analysis has been a frontrunner for many years, and now we are seeing things like text from electronic health records beginning to play a larger role.”

A place to meet and learn from each other

HealthAI will hold its first meeting on 8 September 2026 at AIAS, where researchers can attend presentations and meet others with an interest in AI in health.

The primary ambition is to create a forum for knowledge sharing, and the steering group behind the network encourages all researchers across the university to join – whether AI is a tool you use or the main focus of your research.

JOIN THE NETWORK HERE

 

“If we can bring people together and make the research more visible – both to each other and to the outside world – we will already have achieved a great deal,” says Adam Hulman.

There are already clear signs of demand. Even during the process of establishing the network, new connections have emerged.

“One of the members of the new steering group had a PhD student who was looking for colleagues working with speech recognition technology – and my group is actually doing that in one of our projects. That has already led to a couple of meetings and a lab visit. It’s really exciting, and we hope the network can create many more connections like that.”

Stine Korreman also hopes the network will help map existing AI competences at Health.

“This will make it easier for colleagues to discover projects similar to their own across the faculty, and at the same time we would very much like to identify our areas of strength within the field so we can build on them,” she explains.

It’s not about hype

Both co-chairs emphasise that the rapid developments in AI call for a sober, research-based perspective.

“There is a lot of hype around AI these years,” says Adam Hulman.

“The public debate is full of discussions and predictions about how artificial intelligence will change the world. But as researchers, it is our responsibility to carefully test whether and how these technologies can make a measurable difference in healthcare.”

Stine Korreman also points out that the term “artificial intelligence” itself can be misleading.

“I actually think it can hold us back that we tend to talk about the technology as if it were human. In reality, it is advanced statistics powered by computing and data. When we keep that in mind, we become better at both recognising the potential and understanding the limitations.”

A new addition to the network landscape

HealthAI is the newest of a total of nine research networks at Health, all of which have been established over the past seven years.

And according to Stine Korreman, the timing could hardly be better.

“I actually tried to start something similar a few years ago, but at the time there wasn’t really the critical mass needed to get a network off the ground. Today, we are many researchers working with AI in one way or another, so it’s fair to say that the time is right for us to have our own network.”

Contact

Network Coordinator Anja P. Einholm
Aarhus University, Health – Dean’s Office
Mobile: +45 93 50 84 08
Email: ape@au.dk