| Abstract |
This project develops an innovative AI-powered machine learning system for more reliable and early sepsis detection in hospital patients. Designed to address the gap between statistical accuracy and real-world clinical usefulness, the system achieves a 40.5-hour median lead-time, more than doubles detection rates over standard methods, reduces false alarms, and demonstrates reliable performance across hospitals, representing a clinically viable solution for reducing sepsis-related mortality. |
