Scientists have unveiled an artificial intelligence model capable of predicting the likelihood of developing more than 1,000 diseases years before diagnosis, in what they describe as a major step toward preventative healthcare.<\/p>\n\n\n\n
The model, called Delphi-2M, is built on the same transformer technology that powers consumer chatbots like ChatGPT. Instead of processing language, it analyses patient health records to identify patterns in the progression of illnesses, researchers explained in a paper published Wednesday in Nature<\/em>.<\/p>\n\n\n\n The project brought together experts from institutions in the UK, Denmark, Germany, and Switzerland. They trained the system using data from the UK Biobank, a biomedical database covering half a million participants, and later validated its performance against Denmark\u2019s public health records, which hold information on nearly two million people.<\/p>\n\n\n\n \u201cUnderstanding a sequence of medical diagnoses is a bit like learning grammar in a text,\u201d said Moritz Gerstung of the German Cancer Research Center. \u201cDelphi-2M learns how diseases emerge in succession, enabling very meaningful and health-relevant predictions.\u201d<\/p>\n\n\n\n Charts presented by Gerstung suggested the AI could identify individuals at much higher or lower risk of heart attacks than traditional models based solely on age and other standard factors. Unlike existing tools such as Britain\u2019s QRISK3 \u2013 which focuses on heart attack and stroke \u2013 Delphi-2M can estimate risks across a vast range of conditions simultaneously.<\/p>\n\n\n\n However, researchers cautioned that the system remains experimental. They noted that the datasets used to train it are skewed toward certain age groups and ethnicities, limiting how broadly the results can be applied.<\/p>\n\n\n\n \u201cThis is still a long way from improved healthcare,\u201d said Peter Bannister, a fellow at the Institution of Engineering and Technology.<\/p>\n\n\n\n Even so, the team sees significant potential. In the future, Delphi-2M could guide monitoring, enable earlier interventions, and help optimise strained healthcare resources, said co-author Tom Fitzgerald of the European Molecular Biology Laboratory.<\/p>\n\n\n\n Ewan Birney, another co-author, described the tool as \u201ca step toward preventative medicine at scale,\u201d while King\u2019s College London professor Gustavo Sudre called it \u201ca significant advance towards interpretable and ethically responsible predictive modelling.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":" Scientists have unveiled an artificial intelligence model capable of predicting the likelihood of developing more than 1,000 diseases years before 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a million participants<\/h2>\n\n\n\n
System remains experimental<\/h2>\n\n\n\n