Machine learning tool decodes immune receptor sequences to diagnose multiple diseases

Stanford University researchers developed a machine learning-based method capable of diagnosing multiple diseases using B cell and T cell receptor sequences. The model, called Machine learning for Immunological Diagnosis (Mal-ID), distinguished between COVID-19, HIV, lupus, type 1 diabetes, influenza vaccination response, and healthy states, achieving near-perfect classification.