Ran Xiao, assistant professor, and Xiao Hu, professor, recently had their “Generalizability of SuperAlarm via Cross-Institutional Performance Evaluation” manuscript accepted for publication in IEEE Access. The study offers valuable insights into the generalizability of SuperAlarm, a machine-learning based frame that extracts hidden multivariate patterns in multi-modality data streams of modern health enterprise as predictive features for a target clinical endpoint by evaluating its cross-institutional performance in predicting in-hospital code blue events.