报告人：Prof. Karsten Borgwardt

时   间：2022/12/15   16:00 - 17:00

主持人：张牧涵  助理教授

Zoom：

    Zoom ID:  878 5491 9091

    Passcode：PSJAS1215

   https://us06web.zoom.us/j/87854919091?pwd=enBNVTZadyt2RU9rMGxMayttb0FRQT09

Tencent Meeting：

    Meeting ID: 751-521-578

   https://meeting.tencent.com/dm/5fDfRWBUsrnq

Live Stream：

   https://www.koushare.com/lives/room/492569

Title：Machine Learning in Medicine: Sepsis Prediction and Antibiotic Resistance Prediction

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 and the related problem of antibiotic resistance prediction.

Biography:  

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 Euro 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” (2018-2022) and the subsequent National Data Stream on infection-related outcomes in Swiss ICUs (started in 2022), and two Marie Curie Innovative Training Networks on Machine Learning in Medicine (2013-2016 and 2019-2022).