Infectiology++ - Germ Tracking

At a glance

Project leader : Thomas Ott
Deputy of project leader : Stefan Glüge
Project status : completed
Funding partner : Public sector (excl. federal government) (Universitätsspital Zürich)
Project partner : Universitätsspital Zürich, SpinningBytes AG
Contact person : Thomas Ott

Description

In this project, we develop a system for the detection and analysis of germ transmission chains in the University Hospital Zurich. The system is based on an expert system solution in combination with machine learning (reinforcement learning).

Publications

Ott, Thomas; Glüge, Stefan; Schüle, Martin; Hill, Christopher,

2018.

A dynamic network approach for the analysis of pathogen transmission chains.

In:

The 26th Nonlinear Dynamics of Electronic Systems Conference, (NDES 2018), Acireale, 11-13 June 2018.

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