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's predictive capabilities have been validated using data from 1.9 million people in Denmark, where it has shown great accuracy for diseases with clear progression.
The intent is to identify high-risk patients and potentially guide them toward preventative treatments based on calculated risks.
This innovative model could change the landscape of personalized care and health resource planning, heralding a new era in medical predictive analysis.
