Johns Hopkins engineer Suchi Saria has developed an AI-powered platform that is reducing sepsis mortality rates by 18% in dozens of hospitals across the United States—a significant advance in ...

Bayesian Health and Johns Hopkins University Announce Ground-breaking Results in Nature Medicine. ... (TREWS) and resulted in more than 15 publications in top medical and AI journals and conferences.

Patients are 20% less likely to die of sepsis because of a new AI system developed at Johns Hopkins University that catches symptoms hours earlier than traditional methods, an extensive hospital study ...

Johns Hopkins University Summary: Patients are 20% less likely to die of sepsis because a new AI system catches symptoms hours earlier than traditional methods, an extensive hospital study ...

More information: Roy Adams et al, Prospective, multi-site study of patient outcomes after implementation of the TREWS machine learning-based early warning system for sepsis, Nature Medicine (2022 ...

More information: Albert Wu, Factors driving provider adoption of the TREWS machine learning-based early warning system and its effects on sepsis treatment timing, Nature Medicine (2022).DOI: 10. ...