Experience

Treat Systems

• Denmark
• Biotechnology Research
• 1 - 100 Employee

• • Jun 2018 - Present

• • Jun 2016 - Jun 2018

  Project: SepsisFinderThe SepsisFinder project addresses three important events during the course of an infection: recognition of the onset of infection (or early warning), risk assessment and revision of antibiotic therapy. For each case, a model will take routinely available structured patient data into account, combining a causal probabilistic network model of the response to infection with machine learning algorithms and decision theory to provide real-time decision support.



Aalborg University

• Denmark
• Research Services
• 700 & Above Employee

• PhD Student

  • Aug 2012 - Jul 2016

  Thesis: Gradation of the Severity of Sepsis: Learning in a Causal Probabilistic Network Summary: Sepsis is a severe response to infection, characterised by systemic inflammation leading to tissue damage and organ dysfunction. In septic patients, early, appropriate antibiotic treatment is vital, more so in patients with severe sepsis. The aim of the PhD project was to further develop an existing causal probabilistic network (CPN) model of sepsis through learning: both manually through evidence-based adjustments to the model and automatically through machine learning from patient databases. The model forms part of a larger CPN used by the decision support system Treat, which provides advice for optimal antibiotic treatment. The resulting models for the prediction of bacteraemia and 30-day mortality can be used as standalone systems or reintegrated with the Treat decision support system. As a standalone model, the output can be considered as an intelligent biomarker for sepsis, tuned from real patient data. Future work involves the development of a more complete picture of the inflammatory response, including the time-course, which could enable earlier detection of infection or treatment revision in patients for whom infections are not microbiologically documented. Show less



Industrial Research Ltd

• Research Services
• 1 - 100 Employee

• Research Scientist

  • Nov 2010 - Aug 2011

  Heat transfer in liquid-nitrogen-cooled transformer windings Heat transfer in liquid-nitrogen-cooled transformer windings


University of Canterbury
• New Zealand
• Higher Education
• 700 & Above Employee
• Tutor - Department of Mathematics and Statistics

  • Jun 2009 - Nov 2010
• Research Assistant

  • Nov 2009 - Feb 2010