Improve and accelerate how we learn from health data: New approach reduces machine learning time by 60%

Electronic health records, like ELGA in Austria, provide an overview of laboratory results, diagnostics and therapies. Much could be learned from the personal and private data of individuals – with the help of machine learning – for use in the treatment of others. However, the use of the data is a delicate matter, especially when it comes to diseases that carry a stigma. Researchers involved in the EU project “Enabling the Big Data Pipeline Lifecycle on the Computing Continuum (DataCloud)” are working to make new forms of information processing suitable for medical purposes. Dragi Kimovski and his colleagues recently presented their findings in a publication.

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Working towards the full exploitation of 5G potential: Research team creates “Carinthian Fog”

The 5G Playground Carinthia provides researchers with an open laboratory to explore the possibilities of this new mobile technology. There is a hitch: Although 5G facilitates the rapid transmission of large amounts of data, this data also needs to be processed. Outsourcing this computing power to a cloud data centre results in time lags. Using what is known as “Carinthian Fog”, a research team funded by the Austrian Research Promotion Agency (FFG) seeks to develop an alternative that can move data processing closer in terms of distance.

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Research into COVID-19-related crisis scenarios at AAU: New technology will optimise the supply of medical protective equipment

Earlier this year, it became painfully clear to many in Europe that the supply of face masks, gloves and protective overalls is by no means crisis-proof. A research team consisting of Austrian and Chinese scientists is now working on new technologies that will address different levels of the supply chain and will ultimately lead to the faster, more efficient and cheaper supply of protective equipment across Europe, even in times of crisis.

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Data pipelines: New measures to tackle the last few congested metres

Today’s data networks are well developed: Even so, although the data can pass through the pipelines smoothly and largely unhindered, the last few metres of the pipeline represent a bottleneck. Firewalls, security and the restrictions imposed by the processing software all tend to slow down processing. Now, thanks to a new H2020 project, a research team at the Department of Information Technology, led by Radu Prodan, has started to work on new measures aimed at tackling the last few congested metres. 

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