Artificial intelligence may soon be able to predict your future health years in advance – much like a weather forecast.
Scientists say a new AI model can analyze medical records and estimate the risk of more than 1,200 different diseases, sometimes up to a decade ahead.
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A “Health Forecast” Model
The system, called Delphi-2M, works in a similar way to AI chatbots such as ChatGPT. Instead of predicting the next word in a sentence, it looks for patterns in anonymized medical data to predict health outcomes.
Rather than predicting an exact date for an illness – like a heart attack on October 1 – the AI generates probabilities, such as a 70% chance of developing type 2 diabetes within the next five years.
“This is like weather forecasting, but for healthcare,” explained Prof. Ewan Birney, interim executive director of the European Molecular Biology Laboratory.
“And it’s not just for one disease at a time – it’s for all of them together. That’s something we’ve never been able to do before.”
How It Was Built
The model was trained using data from over 400,000 people in the UK Biobank project, which includes hospital records, GP visits, and lifestyle factors such as smoking habits.
It was then tested on additional UK data and more than 1.9 million health records from Denmark. According to Prof. Birney, the predictions held up well:
“If the model says there’s a one-in-10 risk in the next year, that’s what we see happen.”
The tool is strongest at forecasting conditions with clear progression, such as type 2 diabetes, heart attacks, and sepsis, rather than unpredictable infections.
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What Could This Mean for Patients?
The goal is not to scare people with predictions but to spot risks early so steps can be taken to prevent disease. For example:
- Patients at high risk of liver disease might be advised to cut back on alcohol.
- Those likely to develop heart disease could be offered statins or lifestyle programs earlier.
Hospitals could also use the tool to plan resources by forecasting healthcare demand. Imagine predicting how many heart attacks a city might face in 2030 and preparing staff and equipment accordingly.
“This could mark the beginning of a new way to understand human health,” said Prof. Moritz Gerstung of the German Cancer Research Centre.
What’s Next?
For now, Delphi-2M is still in the research stage and not ready for clinical use. Experts stress it must be tested, refined, and carefully regulated before being rolled out in hospitals.
Some limitations also remain. The UK Biobank data mostly covers people aged 40 to 70, which may introduce bias. Researchers are now working to include genetic data, imaging, and blood tests to strengthen predictions.
Even with these challenges, scientists believe this technology could follow a path similar to genomics, which took about a decade to move from research to routine healthcare use.
“This is research, but the technology is here,” Prof. Birney emphasized. “We just need to make sure it’s safe, accurate, and fair before it reaches patients.”