11/20/22 Healthcare In Europe – Early detection of sepsis with the help of AI
Suchi Saria, PhD, director of the Machine Learning and Healthcare Lab at Johns Hopkins, who led this work, explains that TREWS automatically and continuously monitors disparate clinical data, including vital signs, laboratory data, medication history, procedure and clinical history, and physician notes. It generates a continuous real-time “sepsis score” that can trigger an alert to healthcare staff. Clinical caregivers can analyse why the TREWS alert was generated, accept or dismiss it, and initiate timely treatment on patients confirmed to be septic.
‘Our results showing high physician adoption and associated mortality and morbidity reductions are a milestone for the field of AI,’ comments Saria. ‘They are the culmination of nearly a decade of significant technological investment, deep collaboration, the development of novel techniques, and rigorous evaluation. Further, what’s most exciting here is that this approach is applicable not just to sepsis but to many other critical complications.’
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