Post by Samson Abanni (@Abanni)

Researchers have developed machine learning models that analyze "proteomic signatures"—patterns of 3,000 proteins in the blood—to predict the onset of 1,183 diseases up to a decade before clinical diagnosis. Using data from the UK Biobank, the models outperformed traditional clinical risk factors (like age, BMI, and cholesterol) for a vast range of conditions, including rare cancers and neurological disorders. The core technical breakthrough is the transition from monitoring single biomarkers

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