Research from UK Biobank claims an artificial intelligence programme can estimate the risk of more than 1,000 diseases and scientists say it could be used by doctors in the next five to 10 years.
A new AI tool could be used by doctors to predict when someone will get cancer or have a heart attack.
Research shows the artificial intelligence programme can estimate the risk of more than 1,000 diseases and scientists say it could be used by doctors in the next five to 10 years. They have trained and tested the model using anonymised patient record data to help predict what might happen to people over the next decade and beyond.
Ewan Birney, director at the European Molecular Biology Laboratory (EMBL), who worked on the research, said: “The future – and this is five to 10 years away – is when clinicians are enhanced and supported by these sophisticated AI tools.
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“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.”
The AI was trained on anonymised patient data from 400,000 people from the UK Biobank. Researchers then tested the model using data from 1.9 million patients in the Danish National Patient Registry.
The model works by assessing the probability of whether – and when – people may develop diseases such as cancer, diabetes, cardiovascular disease and respiratory disease. Health risks are expressed as rates over time, similar to forecasting a 70% chance of rain.
The tool was better at offering predictions for conditions with clear progression patterns, such as certain types of cancer and heart attacks. It was less reliable for conditions that may be variable, such as mental health problems or pregnancy-related complications.
Moritz Gerstung, head of the division of AI in oncology at the German Cancer Research Centre, who worked on the study, 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.
“By learning from large populations, these models offer a powerful lens into how diseases unfold, and could eventually support earlier, more tailored interventions.”
The tool was fed data and looked for “medical events” in people’s history, such as when illnesses were diagnosed, together with lifestyle factors such as whether people were obese, smoked or drank alcohol, plus their age and sex. It learned to forecast disease risk from the order in which such events happened and how much time had passed between them.
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The study, published in the journal Nature, concluded: “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.
Its generative nature also enables sampling of synthetic future health trajectories, providing meaningful estimates of potential disease burden for up to 20 years.”