AI can be good for our health and wellbeing

In 2024, Professor Zoe Kourtziin the Department of Psychology showed that an AI tool developed by her team could outperform clinical tests at predicting whether people with early signs of dementia will remain stable or develop Alzheimer's disease.

At a time of intense pressure on the NHS, tools such as this could help doctors prioritise care for those patients who need it most, while removing the need for invasive and costly diagnostic tests for those whose condition will remain stable. They can also give patients peace of mind that their condition is unlikely to worsen, or, for those less fortunate, it can help them and their families prepare.

These tools could also be transformational in the search for new drugs, making clinical trials more effective, faster and cheaper, says Kourtzi.

Recently, two dementia drugs - lecanemab and donanemab - have shown promise in slowing the disease, but the benefits compared to the costs were judged insufficient to warrant approval for use within the NHS. Beyond these, there's been limited progress in the field.

Part of the problem is that clinical trials often focus on the wrong people, which is where AI may help to better decide who to include in trials.

"If you have people that the AI models say will not develop pathology, you won't want to put them in your trial. They'll only mess up the statistics, and then [the trials] will never show an effect, no matter if you have the best drug in the world. And if you include people who will progress really fast, it might be already too late for the drug to show benefit."

Kourtzi is leading one of ai@cam's AI-deas projects to create a 'BrainHealth hub' to tackle the global brain and mental health crisis. It will bridge the gap between engineers, mathematicians and computer scientists who have the tools but lack the data, and clinicians and neuroscientists who have the data but lack advanced tools to mine them.

"Our idea is to create a 'hothouse' of ideas where people can come together to ask and answer challenging questions."

University researchers, industry partners, the charity sector and policymakers will explore questions such as: how can we use AI for drug discovery, to accelerate clinical trials and develop new treatments, and how can we build interpretable AI models that can be translated to clinical tools?"

The need for such AI to be reliable and responsible is a theme that comes up frequently when Kourtzi speaks to patient groups.

"When doctors are using a complex diagnostic tool like an MRI machine, patients don't query whether they understand what's in this machine, why it works this way. What they want to know is that it's gone through regulatory standards, it's safe to use and can be trusted. It's exactly the same with AI."