Machine Learning in Medicine: Early Recognition of Sepsis
Karsten Borgwardt
April 14, 2021, Wednesday, 3:00 PM - 4:00 PM EDT
Abstract
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.
Bio
Karsten M. Borgwardt is Professor of Data Mining in the Department Biosystems at ETH Zurich. He studied Computer Science at the Ludwig-Maximilians-Universitat in Munich, completed a Masters in Biology at the University of Oxford, and the PhD at the Ludwig-Maximilians-Universitat in Munich. He works towards two central goals: To enable the automatic generation of new knowledge from big data through machine learning, and to gain an understanding of the relationship between the function of biological systems and their molecular properties. Since 2018 onwards, he coordinates the "Personalised Swiss Sepsis Study", a research network for biomarker discovery in sepsis in Switzerland. In January 2018, Focus Magazine listed him as one of "25 Germans who will shape the next 25 years."