Artificial intelligence can predict people's health problems over a decade into the future, say scientists.
The technology has learned to spot patterns in people's medical records to calculate their risk of more than 1,000 diseases.
The researchers say it is like a weather forecast that anticipates a 70% chance of rain – but for human health.
Their vision is to use the AI model to spot high-risk patients to prevent disease and to help hospitals understand demand in their area, years ahead of time.
The model – called Delphi-2M - uses similar technology to well-known AI chatbots like ChatGPT.
Delphi-2M has been trained to find patterns in anonymous medical records so it can predict what comes next and when.
It doesn't predict exact dates, like a heart attack on October 1, but instead estimates the likelihood of 1,231 diseases.
So, just like weather, where we could have a 70% chance of rain, we can do that for healthcare, Prof Ewan Birney, the interim executive director of the European Molecular Biology Laboratory, said.
The AI model was initially developed using anonymous UK data - including hospital admissions, GP records and lifestyle habits such as smoking - collected from more than 400,000 people as part of the UK Biobank research project.
The model is best at predicting diseases that have a clear disease progression, rather than more random events like infections.
People are already offered a cholesterol-lowering statin based on a calculation of their risk of a heart attack or stroke. The AI tool is not ready for clinical use, but the plan is to use it in a similar way, to spot high-risk patients while there is an opportunity to intervene early and prevent disease.
This is the beginning of a new way to understand human health and disease progression.
The study was a collaboration between the European Molecular Biology Laboratory, the German Cancer Research Centre (DKFZ) and the University of Copenhagen.
