Intensive care units: an automated alert system
Author
Prof. Emanuela Keller
UniversitätsSpital Zürich
Reduce false alarms, predict critical complications: this could improve patient safety and this is where the project “ICU Cockpit” comes in.
About the project
Related links
- description of the project on www.nrp75.ch
- Key data and publications
- Big Data makes intensive care better, press release (2 December 2019)
- Blog post by Emanuela Keller on 15 January 2019 (in German)
- Blog post by Emanuela Keller on 13 November 2018 (in German)
- Schwab P, Keller E, Muroi C, Mack DJ, Strässle C, Karlen W (2018) Not to cry wolf: distantly supervised multitask learning in critical care. Proc 35th Int Conf Mach Learn (ICML), 80:4518-27
- Muroi C, Meier S, De Luca V, Mack DJ, Strässle C, Schwab P, Karlen W, Keller E (2019) Automated false alarm reduction in a real-life intensive care setting using motion detection. Neurocrit Care, Epub ahead of print, DOI:10.1007/s12028-019-00711-w
- Hostettler I C, Richter JK, Schmid J, Neidert M C, Seule M, Boss O, Pangalu A, Germans M R, Muroi C, Keller E (2018) Decision tree analysis in subarachnoid hemorrhage – Prediction of outcome parameters during the course of aneurysmal subarachnoid hemorrhage using decision tree analysis. J of Neurosurgery, 129(6):1499-1510, DOI: 10.3171/2017.7