In brief
Scientists have developed an AI model, Delphi-2M, which can predict health risks for over 1,000 diseases, much like weather forecasts. By analyzing patterns in medical records, this innovative tool aims to identify high-risk patients and assist healthcare systems in resource planning. While still in research phases, the model shows promising results, particularly in predicting diseases with clear progression paths.
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. AI chatbots are trained to understand patterns of language so they can predict the sequence of words in a sentence.
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, told me.
And we can do that not just for one disease, but all diseases at the same time - we've never been able to do that before. I'm excited, he 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 was then tested to see if its predictions stacked up using data from other Biobank participants, and then with 1.9 million people's medical records in Denmark.
It's good, it's really good in Denmark, says Prof Birney.
If our model says it's a one-in-10 risk for the next year, it really does seem like it turns out to be one in 10.
The AI tool, while not yet ready for clinical use, aims to identify high-risk patients, enabling preventative measures such as medication and lifestyle changes.
This is the beginning of a new way to understand human health and disease progression, said Prof Moritz Gerstung, head of the division of AI in oncology at DKFZ, the German Cancer Research Centre.
Though still in the research phase, the potential for implementation in clinical settings is promising. The model aims to enhance healthcare resource planning by predicting demand for medical services, thus revolutionizing disease prevention and treatment strategies.
