Machine Learning Maps Immune Response Changes in Sepsis Patients

Researchers at King's College London used machine learning to identify three distinct temporal immune states in sepsis patients, published in the journal Immunity on August 29, 2026.

The study analyzed blood samples from critically ill patients at Guy's and St Thomas' NHS Foundation Trust to map immune trajectories that do not align with clinical stages.

These findings aim to improve patient outcomes by identifying specific immune response phases, potentially guiding more effective treatment timing for the 21 million annual sepsis deaths worldwide.