Now researchers at Stanford Medicine have devised a way to mine this rich internal database to diagnose diseases as diverse as diabetes COVID-19 responses to influenza vaccines. Although they envision the approach as a way to screen for multiple diseases simultaneously, the machine-learning-based technique can also be optimized to detect complex, difficult-to-diagnose autoimmune diseases such as lupus.

In a study of nearly 600 people—some healthy, others with infections including COVID-19 or autoimmune diseases including lupus and type 1 diabetes—the algorithm the researchers developed, called Mal-ID for machine learning for immunological diagnosis, was remarkably successful in identifying who had what based only on their B and T cell receptor sequence and structures.