Machine Learning in Medicine: Early Recognition of Sepsis

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Sepsis is a major cause of mortality in intensive care units around the world. If recognized early, it can often be treated successfully, but early prediction of sepsis is an extremely difficult task in clinical practice. The data wealth from intensive care units that is increasingly becoming available for research now allows to study this problem of predicting sepsis using machine learning and data mining approaches. In this talk, I will describe our efforts towards data-driven early recognition of sepsis.

Karsten Borgwardt is Full Professor of Data Mining at ETH Zürich, in the Department of Biosystems located in Basel. His work won several awards, including the 1 million EUR Krupp Award for Young Professors in 2013 and a Starting Grant 2014 from the ERC-backup scheme of the Swiss National Science Foundation. Prof. Borgwardt has been and is leading large national and international research consortia, including the “Personalized Swiss Sepsis Study” (2018-2021) and two Marie Curie Innovative Training Networks on Machine Learning in Medicine (2013-2016 and 2019-2022). In its January 12, 2018 edition, German News Magazine FOCUS included him in a list of "25 individuals who could shape the next 25 years".