Detail

Keywords

Attitude to Computers; Automatic Data Processing; Body Temperature Changes; Computer Literacy; Data Interpretation, Statistical; Data Mining; Database Management Systems; Decision Making, Computer-Assisted; Decision Support Techniques; Diagnosis, Computer-Assisted; Drug Therapy, Computer-Assisted; Human-computer Interaction; Hypothermia; Statistics; Therapy, Computer-Assisted; Thermometers

Research group(s)

• AG Daten
  Head: Oliver Kimberger
  Research Area: Perioperative Data Science
  Members:
  Oliver Kimberger
  Stefan Bartos
  Christoph Dibiasi
  Fabian Peter Hammerle
  Daniel Laxar
  Maleczek Mathias

Research interests

My main research focus is the application/implementation of novel data processing technology in the field of perioperative data science for decision support, disease detection and prevention and - ultimately - establishment of personalized medicine via "virtual twin" concepts and also includes human/computer interaction. 

Additionally my research interests include hypothermia research (accidental and therapeutic),  methods for the conservation of normothermia and measurement of core temperature. 

Techniques, methods & infrastructure

Perioperative Data Science Lab with access to supercomputing, "big data" processing, data mining analytics, AR/VR methodology in collaboration with the LBI for Digital Health and Patient Safety. 

Selected publications

1. Laxar, D. et al. (2023) ‘The influence of explainable vs non-explainable clinical decision support systems on rapid triage decisions: a mixed methods study’, BMC Medicine, 21(1). Available at: http://dx.doi.org/10.1186/s12916-023-03068-2.
2. Wallisch, C. et al. (2021) ‘Development and internal validation of an algorithm to predict intraoperative risk of inadvertent hypothermia based on preoperative data’, Scientific Reports, 11(1). Available at: http://dx.doi.org/10.1038/s41598-021-01743-z.
3. Dibiasi, C. et al. (2023) ‘Predicting Intraoperative Hypothermia Burden during Non-Cardiac Surgery: A Retrospective Study Comparing Regression to Six Machine Learning Algorithms’, Journal of Clinical Medicine, 12(13), p. 4434. Available at: http://dx.doi.org/10.3390/jcm12134434.
4. Bologheanu, R. et al., 2021. A retrospective study of sugammadex for reversal of neuromuscular blockade induced by rocuronium in critically ill patients in the ICU. Available at: http://dx.doi.org/10.1038/s41598-022-04818-7.
5. Maleczek, M. et al. (2023) ‘Intraoperative Hypotension Is Associated with Postoperative Nausea and Vomiting in the PACU: A Retrospective Database Analysis’, Journal of Clinical Medicine, 12(5), p. 2009. Available at: http://dx.doi.org/10.3390/jcm12052009.