AI-driven Early Warning Systems for Sepsis Detection and Intervention in Critical Care Settings
Abstract
This research paper introduces AI-driven early warning systems for sepsis detection and intervention in critical care settings. By analyzing streaming physiological data, laboratory results, and clinical notes, our system detects early signs of sepsis, predicts patient deterioration, and triggers timely interventions, such as antibiotic administration and fluid resuscitation. Implementation of this system improves sepsis recognition, reduces sepsis-related mortality, and enhances patient outcomes in intensive care units.
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