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A revolutionary artificial intelligence tool, Delphi-2M, is showing great potential in predicting diseases with clear progression, such as type 2 diabetes and heart attack.
It can predict the risk of over 1,000 diseases, including cancer and cardiovascular disease, even decades before they appear.
Researchers from the European Molecular Biology Laboratory (EMBL), the German Cancer Research Center, and the University of Copenhagen hope that the technology will help in the early identification of high-risk patients, enabling disease prevention.
Delphi-2M is trained on millions of anonymized medical records and analyzes health history and lifestyle habits, such as smoking, alcohol consumption, or obesity.
It can predict an individual's health up to 20 years later.
The tests were conducted on data from 400,000 patients from the UK Biobank project and 1.9 million people from the Danish national registry.
“Medical events often follow predictable patterns.
"Our model learns them and can predict future health outcomes," explained Thomas Fitzgerald, co-author of the study published in the journal Nature.
Experts expect the tool to become a daily part of doctors' work.
“You walk into the office and get a clear picture: the four biggest risks and two things you can do to reduce them,” said Prof. Ewan Birney, executive director of EMBL.
However, experts warn of its limitations. “The model reproduces biases from the data, including age, ethnicity and health outcomes,” said Prof. Justin Stebbing, a consultant oncologist.
Prof. Peter Bannister added that the main challenge remains ensuring equal access and digital infrastructure for all, not just the wealthy.
Many experts believe this is just the beginning.
Future versions of Delphi-2M could integrate biomarkers, imaging, and genetic data, transforming it into a powerful precision medicine tool.
The discovery comes as the One Cancer Voice organization warns that cancer cases will reach record levels by 2040, with one person diagnosed every two minutes and unprecedented increases in breast, prostate and lung cancer.
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