Food allergy represents an increasing global health issue, significantly impacting society on a personal and on a systems-wide level. The gold standard for diagnosing food allergy, the oral food challenge, is time-consuming, expensive, and carries risks of allergic reactions, with unpredictable severity. There is, therefore, an urgent need for more accurate, scalable, predictive diagnostic techniques.
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