Scientists have developed a new artificial intelligence tool that can predict your personal risk of more than 1,000 diseases, and forecast changes in health a decade in advance.
The generative AI tool was custom-built by experts from the European Molecular Biology Laboratory (EMBL), the German Cancer Research Centre and the University of Copenhagen, using algorithmic concepts similar to those used in large language models (LLMs).
It is one of the most comprehensive demonstrations to date of how generative AI can model human disease progression at scale, and was trained on data from two entirely separate healthcare systems.
Details of the breakthrough were published in the journal Nature.
“Medical events often follow predictable patterns,” said Tomas Fitzgerald, a staff scientist at EMBL’s European Bioinformatics Institute (EMBL-EBI). “Our AI model learns those patterns and can forecast future health outcomes.”
The tool works by assessing the probability of whether – and when – someone may develop diseases such as cancer, diabetes, heart disease, respiratory disease and many other disorders.
Named Delphi-2M, it looks for “medical events” in a patient’s history, such as when illnesses were diagnosed, together with lifestyle factors such as whether they are or were obese, smoked or drank alcohol, plus their age and sex.
The tool also looks at anonymised patient record data to predict what might happen over the next decade and beyond.
The tool was trained and tested on anonymised patient data from 400,000 people in the UK Biobank study and 1.9 million patients in the Danish national patient registry.
Health risks are expressed as rates over time, similar to forecasting a 70% chance of rain at the weekend.
Ewan Birney, the EMBL interim executive director, said patients might be able to benefit from the tool within the next few years.
“You walk into the doctor’s surgery and the clinician is very used to using these tools, and they are able to say: ‘Here’s four major risks that are in your future and here’s two things you could do to really change that.’
“I suspect everyone will be told to lose weight, and if you smoke you will be told to stop smoking – and that will be in your data so that advice isn’t going to change remarkably – but for some diseases I think there will be some very specific things. That’s the future we want to create.”
He said the advantage of the new AI tool over existing ones – such as the Qrisk method of calculating risk of having a heart attack or stroke over the next decade – was “we can do all diseases at once and over a long time period. That is the thing that single disease models can’t do.”
The team said: “Delphi-2M predicts the rates of more than 1,000 diseases, conditional on each individual’s past disease history, with accuracy comparable to that of existing single-disease models.
“Delphi-2M’s generative nature also enables sampling of synthetic future health trajectories, providing meaningful estimates of potential disease burden for up to 20 years.”
Prof Moritz Gerstung, the head of the division of AI in oncology at the German Cancer Research Centre, said: “This is the beginning of a new way to understand human health and disease progression.
“Generative models such as ours could one day help personalise care and anticipate healthcare needs at scale.”
