"The tool works by assessing the probability of whether and when someone may develop diseases such as cancer, diabetes, heart disease, respiratory disease and many other disorders. Named Delphi-2M, it looks for medical events in a patient's history, such as when illnesses were diagnosed, together with lifestyle factors such as whether they are or were obese, smoked or drank alcohol, plus their age and sex."
"Medical events often follow predictable patterns, said Tomas Fitzgerald, a staff scientist at EMBL's European Bioinformatics Institute (EMBL-EBI). Our AI model learns those patterns and can forecast future health outcomes. The tool was trained and tested on anonymised patient data from 400,000 people in the UK Biobank study and 1.9 million patients in the Danish national patient registry. Health risks are expressed as rates over time, similar to forecasting a 70% chance of rain at the weekend."
The AI model Delphi-2M predicts individual risk trajectories for more than 1,000 diseases and can forecast health changes up to a decade ahead. It was developed using algorithmic concepts similar to large language models and trained on anonymised health records from 400,000 UK Biobank participants and 1.9 million patients in the Danish national patient registry. The model assesses timing and probability of conditions such as cancer, diabetes, heart and respiratory disease by analyzing medical event sequences, diagnoses timing, lifestyle factors (obesity, smoking, alcohol), age and sex. Outputs present risk as time-based rates to inform clinical decisions.
Read at www.theguardian.com
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