Predicting the onset of sepsis with machine learning
The early recognition of sepsis remains a key challenge in healthcare. Since 2018, Karsten Borgwardt from D-BSSE and Adrian Egli from the University Hospital Basel have coordinated the Personalized Swiss Sepsis Study, a multidisciplinary consortium that tries to predict the onset of sepsis through machine learning on the vast volume of data from intensive care units and clinical laboratories. The consortium’s research and infrastructure is now described on a one-stop platform.
The external pagePersonalized Swiss Sepsis Study (PSSS)call_made is co-funded by the external pageSwiss Personalized Health Network (SPHN)call_made and the external pagePersonalized Health and Related Technologies (PHRT)call_made, which is a strategic focus area of the ETH Domain.